This document describes a study that developed algorithms to optimize routing for fecal sludge collection trucks in Nonthaburi, Thailand. Geographic Information Systems (GIS) and Tabu Search optimization were used to analyze GPS tracking data from collection trucks and generate optimal routes. The algorithms consider multiple routes, time windows, distance costs, vehicle capacity, and priority of customers needing immediate service. Testing showed the optimized routes reduced traveling distances by half compared to actual routes and ensured maximum use of vehicle capacity.
Large cities in developing countries are characterized by growth in automobile ownership, insufficient
transportation infrastructure and service development. These cities often suffer from congestion, poor mobility
and accessibility, significant economic waste, adverse environmental impact and safety problems. This paper
focuses on identification of travel time characteristics and other traffic parameters and to develop a predictive
model for travel time on Akure major roads. Data on travel time were collected for vehicles during the morning
and evening peak periods using floating car technique. The data was analyzed using Statistical Packages for
Social Sciences (SPSS) and fitted into Multiple Regression model to establish a relationship between the
Travel Time and other road traffic parameters. Travel time (Tt) was modeled as a function of section length
(X1), number of intersections (X2), pedestrian/ economic activities (X3), Traffic volume (X4), enforcement
agency (X5) and road width (X6). The Coefficient of multiple determination R2 was 0.702 which means that
there is 70.2% of the dependent variable (travel time) in the forward direction as explained (accounted) by the
independent variables and 72.2% in the opposite direction. The result revealed that section length, pedestrian
economic activity and traffic volume were all significant at 5% level and has a positive relationship with travel
time in both forward and reverse direction. The model identifies the impact of these traffic parameters on travel
time and recommend measures for improvement.
Determination of congestion charge for car users in cbd area of thiruvanantha...eSAT Journals
Abstract Congestion is a situation in which demand for road space exceeds supply and is characterized by slower speeds, longer trip times, higher transportation costs and increased vehicular queuing. Thiruvananthapuram, the capital city of Kerala, is the second largest and most populous city in the state.The roads and neighbourhoods of the city experiences more chronic congestion and serious crashes than ever before due to higher share of personalized transport and para-transit modes in traffic stream. The present study conducted in Central Business District (CBD) area of Thiruvananthapuram city. The periods of peak congestion in Thiruvananthapuram now last for 4 hours from 8.00 to 10.00 in the morning and from 4.00 to 6.00 in the evening. In this paper, an attempt has been made to assess the congestion level experienced on major road corridors of the city and to determine congestion charge for car users in Mahatma Gandhi Road, which is the most congested road corridor of Thiruvanathapuram city. The method used for the determination of optimal pricing is related to the point of pricing where the external costs are met by the revenue generated by the pricing level. Keywords: Congestion pricing, External costs of congestion, Travel time, Demand elasticity.
Impact of Different Types of Land Use on Transportation System of Dhaka City ...Shahadat Hossain Shakil
Land use distribution and transportation both are very important issue for Dhaka city in recent period. To relate these two issues with each other is also a very effective job but a difficult one indeed. This study intends to find out the impact of different land use changes on the transportation system of Dhaka city. One of the most important roads of Dhaka city, Mirpur Road has been taken to understand and to analyze for this study. This study will help to take significant decisions and generate proper policies in transportation sector. It will also contribute to the attempts of combining land use planning and transportation planning. By assessing the land use change impact on transportation system, traffic management, congestion control and improvement of road network will be possible to make
Public Transport Accessibility Index for Thiruvananthapuram Urban AreaIOSR Journals
Transportation planning is an important part in the development of a region. An effective transport
system and associated urban forms will improve the economic and social opportunities. Accessibility and
mobility are the two main parameters which contribute to the effective transportation system. In this paper, the
accessibility to the public transportation system is identified for the selected study area with the help of an
indexing system. The sub-area in the region was thus graded based on their accessibility and the obtained
values are found to resemble the real world.
Accessibility, indexing system, public transport system, transport planning
Large cities in developing countries are characterized by growth in automobile ownership, insufficient
transportation infrastructure and service development. These cities often suffer from congestion, poor mobility
and accessibility, significant economic waste, adverse environmental impact and safety problems. This paper
focuses on identification of travel time characteristics and other traffic parameters and to develop a predictive
model for travel time on Akure major roads. Data on travel time were collected for vehicles during the morning
and evening peak periods using floating car technique. The data was analyzed using Statistical Packages for
Social Sciences (SPSS) and fitted into Multiple Regression model to establish a relationship between the
Travel Time and other road traffic parameters. Travel time (Tt) was modeled as a function of section length
(X1), number of intersections (X2), pedestrian/ economic activities (X3), Traffic volume (X4), enforcement
agency (X5) and road width (X6). The Coefficient of multiple determination R2 was 0.702 which means that
there is 70.2% of the dependent variable (travel time) in the forward direction as explained (accounted) by the
independent variables and 72.2% in the opposite direction. The result revealed that section length, pedestrian
economic activity and traffic volume were all significant at 5% level and has a positive relationship with travel
time in both forward and reverse direction. The model identifies the impact of these traffic parameters on travel
time and recommend measures for improvement.
Determination of congestion charge for car users in cbd area of thiruvanantha...eSAT Journals
Abstract Congestion is a situation in which demand for road space exceeds supply and is characterized by slower speeds, longer trip times, higher transportation costs and increased vehicular queuing. Thiruvananthapuram, the capital city of Kerala, is the second largest and most populous city in the state.The roads and neighbourhoods of the city experiences more chronic congestion and serious crashes than ever before due to higher share of personalized transport and para-transit modes in traffic stream. The present study conducted in Central Business District (CBD) area of Thiruvananthapuram city. The periods of peak congestion in Thiruvananthapuram now last for 4 hours from 8.00 to 10.00 in the morning and from 4.00 to 6.00 in the evening. In this paper, an attempt has been made to assess the congestion level experienced on major road corridors of the city and to determine congestion charge for car users in Mahatma Gandhi Road, which is the most congested road corridor of Thiruvanathapuram city. The method used for the determination of optimal pricing is related to the point of pricing where the external costs are met by the revenue generated by the pricing level. Keywords: Congestion pricing, External costs of congestion, Travel time, Demand elasticity.
Impact of Different Types of Land Use on Transportation System of Dhaka City ...Shahadat Hossain Shakil
Land use distribution and transportation both are very important issue for Dhaka city in recent period. To relate these two issues with each other is also a very effective job but a difficult one indeed. This study intends to find out the impact of different land use changes on the transportation system of Dhaka city. One of the most important roads of Dhaka city, Mirpur Road has been taken to understand and to analyze for this study. This study will help to take significant decisions and generate proper policies in transportation sector. It will also contribute to the attempts of combining land use planning and transportation planning. By assessing the land use change impact on transportation system, traffic management, congestion control and improvement of road network will be possible to make
Public Transport Accessibility Index for Thiruvananthapuram Urban AreaIOSR Journals
Transportation planning is an important part in the development of a region. An effective transport
system and associated urban forms will improve the economic and social opportunities. Accessibility and
mobility are the two main parameters which contribute to the effective transportation system. In this paper, the
accessibility to the public transportation system is identified for the selected study area with the help of an
indexing system. The sub-area in the region was thus graded based on their accessibility and the obtained
values are found to resemble the real world.
Accessibility, indexing system, public transport system, transport planning
Identification of Factors to Improve Public Transit Services (A Case Study of...Dr. Amarjeet Singh
This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long.
Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.
Posters summarizing dissertation research projects - presented by MSc students at the Institute for Transport Studies (ITS), University of Leeds, April 2017. http://bit.ly/2re35Cs
www.its.leeds.ac.uk/courses/masters/dissertation
Robust Counterpart Open Capacitated Vehicle Routing (RC-OCVRP) Model in Opti...IJECEIAES
In this paper, the Robust Counterpart Open Capacitation Vehicle Rounting Problem (RC-OCVRP) Model has been established to optimize waste transport in districts Sako and districts Sukarami, Palembang City. This model is completed with the aid of LINGO 13.0 by using Branch and Bound solver to get the optimum route. For Sako districs, the routes are as follows: working area 1 is TPS 1-TPS 2-TPS 3-TPA with distance 53.39 km, working area 2 is TPS 1-TPS 2-TPS 3-TPA with distance 48.14 km, working area 3 is TPS 1-TPA with a distance of 22.98 km, and working area 4 is TPS 1-TPS 2TPS 3-TPS 4-TPA with 45.45 km distance, and obtained the optimum route in Sukarami districts is as follows: working area 1 is TPS 1-TPS 2-TPA 44.39 km, working area 2 is TPS 1-TPS 2-TPS 3-TPA with distance 49.32 km, working area 3 is TPS 1-TPS 3-TPA-TPS 2-TPA with distance 58.57 km, and working area 4 is TPS 1-TPA with a distance of 24.07 km, working area 5 is TPS 1-TPS 3-TPA-TPS 2-TPS 4-TPA with a distance of 77.66 km, and working area 6 is a TPS 1-TPS 2-TPS 3-TPA with a distante 44.94 km.
Route optimization for collection of municipal solid waste in Katpadi, VelloreHarshit Shahi
The project aims to reduce the total distance travelled by the fleet of vehicles for collection of municipal solid waste by planning new collection routes using Vehicle Routing Problem Solver (part of Network Analyst extension) in ArcGIS.
Conflict-free dynamic route multi-agv using dijkstra Floyd-warshall hybrid a...IJECEIAES
Autonomous Guided Vehicle is a mobile robot that can move autonomously on a route or lane in an indoor or outdoor environment while performing a series of tasks. Determination of the shortest route on an autonomous guided vehicle is one of the optimization problems in handling conflict- free routes that have an influence on the distribution of goods in the manufacturing industry's warehouse. Pickup and delivery processes in the distribution on AGV goods such as scheduling, shipping, and determining the route of vehicle with short mileage characteristics, is very possible to do simulations with three AGV units. There is a windows time limit on workstations that limits shipping. The problem of determining the route in this study is considered necessary as a multi-vehicle route problem with a time window. This study aims to describe the combination of algorithms written based on dynamic programming to overcome the problem of conflict-free AGV routes using time windows. The combined approach of the Dijkstra and Floyd-Warshall algorithm results in the optimization of the closest distance in overcoming conflict-free routes.
Demand robust counterpart open capacitated vehicle routing problem time windo...IJECEIAES
Demand robust counterpart-open capacitated vehicle routing problem with time windows and deadline (DRC-OCVRPtw,d) model formed and explained in this paper, is the model used to find the minimum distance and the time needed for vehicles to transport garbage in Sukarami Sub-District, Palembang that consists of the time it takes for the vehicle to pass through the route. Time needed to transport garbage to the vehicle is called time windows. Combination of the thoses times is called deadline. The farther the distance passed by vehicle and the more garbage transported, the longer the deadline is needed. This DRC-OCVRPtw,d model is completed by LINGO 13.0 to obtain the optimal route and time deadline for Sukarami Sub-District. The model shows that the improved model of open vehicle routing problem involving the robustness, time windows and deadline can achieve the optimal routes that enable driver to save operational time in picking up the garbage compared to similar problem not involving no-time windows and deadline stated in previous research.
Improving transport in Malta using GIS and LBSMatthew Pulis
A presentation prepared to the University of Malta as part of my MSc. Informatics. This seminar discusses ways and improvements how can a GIS driven system help and improve the current situation in Malta. This presentation also provides a survey discussing how the Maltese view the public transport and gives out interesting conclusions as to where the GIS needs to tackle. The study focuses mainly on ways as to where and how to improve the routes, promoting cultural places, buses ETA and taxi fleet handling amongst others.
It is about Municipal Solid Waste Management by using GIS. How we will be able to control the cost using GIS. And an case study happened in NAGPUR City.
Gis based multi criteria suitability analysis of community hospitalSourav Bhadra
Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorb itant costs on city budget and damages the environment inevitably. Nowadays, mu lti -attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. To find out a suitable location for Community Hospitals in an urban area, GIS based multicriteria analysis is very helpful and accurate. In this project Ward No-22 in Dhaka City is taken as a study area to do a Suitability Analysis for Community Hospitals.
ACO Based Routing and Euler Walks Routing of Solid Waste Management Transport...AM Publications
Municipal solid waste management (MSWM) is an integral part of urban environmental planning [1,2,3,4 &5]. The characteristics
and quantity of MSW arising from domestic, commercial and industrial activities in a region is not only the result of growing
population, rising standards of living and technology development, but also due to the abundance and type of the region’s natural
resources[4]. The collection, transport, treatment and disposal of solid wastes, particularly wastes generated in medium and large
urban centres, have become a relatively difficult problem to solve. To promote sustainable development, waste management has
evolved into material flow management in many developed countries, and includes careful handling of raw materials and
reduction of emissions as well as climate/environment protection. More than 90% of the MSW generated in India is directly
disposed on land in an unsatisfactory manner .The problem is already acute in cities and towns as disposal facilities have not been
able to keep pace with the quantum of wastes generated. It is common to find large heaps of garbage lying in a disorganized
manner in every nook and corner in large cities. Thus transportation of these wastes in effective way is one of the major problem
in Municipal Solid Waste Management.
There are number of limitations for evaluating sustainability of any transportation
system. Huge research work and studies has been carried regarding sustainable
transportation and sustainability indicators. But the specific decision making
methodologies for sustainability evaluation aligned with sustainability of
transportation system is missing at present. Hence it is required to develop the
framework for assessment of sustainability in terms of performance measures
considering the prefixed goals for the purpose of planning. As a part of Multi Criteria
Decision Making process, the Multi Attribute Utility Technique based methodology is
adopted as the most suitable method. In this paper the sustainability index evaluation
is based on combination of individual performance measures is carried out using Multi
Attribute Utility Technique based methodology for emerging metropolitan city of
Nagpur. The results obtained can be conveniently used in sustainability evaluation
process for any corridor. It can also be utilized for comparing the results obtained
through the sustainability evaluation for different scenarios.
Two design methods were used to quantify the improvements of using geotextiles in pavements. In this study, a comprehensive life cycle cost analysis framework was developed and used to quantify the initial and the future cost of 25 representative low volume road design alternatives. A 50 year analysis cycle was used to compute the cost-effectiveness ratio when geotextiled is used for the design methods. The effects of three flexible pavement design parameters were evaluated; and their impact on the results was investigated.
This white paper presents a spatial decision support system (SDSS) aimed at generating optimized vehicles routes for multiple vehicles routing problems that involves serving the demand located at nodes of a transportation network. The SDSS incorporates MapPointTM (cartography and network data), a database and a metaheuristic developed generate routes.
Identification of Factors to Improve Public Transit Services (A Case Study of...Dr. Amarjeet Singh
This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long.
Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.
Posters summarizing dissertation research projects - presented by MSc students at the Institute for Transport Studies (ITS), University of Leeds, April 2017. http://bit.ly/2re35Cs
www.its.leeds.ac.uk/courses/masters/dissertation
Robust Counterpart Open Capacitated Vehicle Routing (RC-OCVRP) Model in Opti...IJECEIAES
In this paper, the Robust Counterpart Open Capacitation Vehicle Rounting Problem (RC-OCVRP) Model has been established to optimize waste transport in districts Sako and districts Sukarami, Palembang City. This model is completed with the aid of LINGO 13.0 by using Branch and Bound solver to get the optimum route. For Sako districs, the routes are as follows: working area 1 is TPS 1-TPS 2-TPS 3-TPA with distance 53.39 km, working area 2 is TPS 1-TPS 2-TPS 3-TPA with distance 48.14 km, working area 3 is TPS 1-TPA with a distance of 22.98 km, and working area 4 is TPS 1-TPS 2TPS 3-TPS 4-TPA with 45.45 km distance, and obtained the optimum route in Sukarami districts is as follows: working area 1 is TPS 1-TPS 2-TPA 44.39 km, working area 2 is TPS 1-TPS 2-TPS 3-TPA with distance 49.32 km, working area 3 is TPS 1-TPS 3-TPA-TPS 2-TPA with distance 58.57 km, and working area 4 is TPS 1-TPA with a distance of 24.07 km, working area 5 is TPS 1-TPS 3-TPA-TPS 2-TPS 4-TPA with a distance of 77.66 km, and working area 6 is a TPS 1-TPS 2-TPS 3-TPA with a distante 44.94 km.
Route optimization for collection of municipal solid waste in Katpadi, VelloreHarshit Shahi
The project aims to reduce the total distance travelled by the fleet of vehicles for collection of municipal solid waste by planning new collection routes using Vehicle Routing Problem Solver (part of Network Analyst extension) in ArcGIS.
Conflict-free dynamic route multi-agv using dijkstra Floyd-warshall hybrid a...IJECEIAES
Autonomous Guided Vehicle is a mobile robot that can move autonomously on a route or lane in an indoor or outdoor environment while performing a series of tasks. Determination of the shortest route on an autonomous guided vehicle is one of the optimization problems in handling conflict- free routes that have an influence on the distribution of goods in the manufacturing industry's warehouse. Pickup and delivery processes in the distribution on AGV goods such as scheduling, shipping, and determining the route of vehicle with short mileage characteristics, is very possible to do simulations with three AGV units. There is a windows time limit on workstations that limits shipping. The problem of determining the route in this study is considered necessary as a multi-vehicle route problem with a time window. This study aims to describe the combination of algorithms written based on dynamic programming to overcome the problem of conflict-free AGV routes using time windows. The combined approach of the Dijkstra and Floyd-Warshall algorithm results in the optimization of the closest distance in overcoming conflict-free routes.
Demand robust counterpart open capacitated vehicle routing problem time windo...IJECEIAES
Demand robust counterpart-open capacitated vehicle routing problem with time windows and deadline (DRC-OCVRPtw,d) model formed and explained in this paper, is the model used to find the minimum distance and the time needed for vehicles to transport garbage in Sukarami Sub-District, Palembang that consists of the time it takes for the vehicle to pass through the route. Time needed to transport garbage to the vehicle is called time windows. Combination of the thoses times is called deadline. The farther the distance passed by vehicle and the more garbage transported, the longer the deadline is needed. This DRC-OCVRPtw,d model is completed by LINGO 13.0 to obtain the optimal route and time deadline for Sukarami Sub-District. The model shows that the improved model of open vehicle routing problem involving the robustness, time windows and deadline can achieve the optimal routes that enable driver to save operational time in picking up the garbage compared to similar problem not involving no-time windows and deadline stated in previous research.
Improving transport in Malta using GIS and LBSMatthew Pulis
A presentation prepared to the University of Malta as part of my MSc. Informatics. This seminar discusses ways and improvements how can a GIS driven system help and improve the current situation in Malta. This presentation also provides a survey discussing how the Maltese view the public transport and gives out interesting conclusions as to where the GIS needs to tackle. The study focuses mainly on ways as to where and how to improve the routes, promoting cultural places, buses ETA and taxi fleet handling amongst others.
It is about Municipal Solid Waste Management by using GIS. How we will be able to control the cost using GIS. And an case study happened in NAGPUR City.
Gis based multi criteria suitability analysis of community hospitalSourav Bhadra
Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorb itant costs on city budget and damages the environment inevitably. Nowadays, mu lti -attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. To find out a suitable location for Community Hospitals in an urban area, GIS based multicriteria analysis is very helpful and accurate. In this project Ward No-22 in Dhaka City is taken as a study area to do a Suitability Analysis for Community Hospitals.
ACO Based Routing and Euler Walks Routing of Solid Waste Management Transport...AM Publications
Municipal solid waste management (MSWM) is an integral part of urban environmental planning [1,2,3,4 &5]. The characteristics
and quantity of MSW arising from domestic, commercial and industrial activities in a region is not only the result of growing
population, rising standards of living and technology development, but also due to the abundance and type of the region’s natural
resources[4]. The collection, transport, treatment and disposal of solid wastes, particularly wastes generated in medium and large
urban centres, have become a relatively difficult problem to solve. To promote sustainable development, waste management has
evolved into material flow management in many developed countries, and includes careful handling of raw materials and
reduction of emissions as well as climate/environment protection. More than 90% of the MSW generated in India is directly
disposed on land in an unsatisfactory manner .The problem is already acute in cities and towns as disposal facilities have not been
able to keep pace with the quantum of wastes generated. It is common to find large heaps of garbage lying in a disorganized
manner in every nook and corner in large cities. Thus transportation of these wastes in effective way is one of the major problem
in Municipal Solid Waste Management.
There are number of limitations for evaluating sustainability of any transportation
system. Huge research work and studies has been carried regarding sustainable
transportation and sustainability indicators. But the specific decision making
methodologies for sustainability evaluation aligned with sustainability of
transportation system is missing at present. Hence it is required to develop the
framework for assessment of sustainability in terms of performance measures
considering the prefixed goals for the purpose of planning. As a part of Multi Criteria
Decision Making process, the Multi Attribute Utility Technique based methodology is
adopted as the most suitable method. In this paper the sustainability index evaluation
is based on combination of individual performance measures is carried out using Multi
Attribute Utility Technique based methodology for emerging metropolitan city of
Nagpur. The results obtained can be conveniently used in sustainability evaluation
process for any corridor. It can also be utilized for comparing the results obtained
through the sustainability evaluation for different scenarios.
Two design methods were used to quantify the improvements of using geotextiles in pavements. In this study, a comprehensive life cycle cost analysis framework was developed and used to quantify the initial and the future cost of 25 representative low volume road design alternatives. A 50 year analysis cycle was used to compute the cost-effectiveness ratio when geotextiled is used for the design methods. The effects of three flexible pavement design parameters were evaluated; and their impact on the results was investigated.
This white paper presents a spatial decision support system (SDSS) aimed at generating optimized vehicles routes for multiple vehicles routing problems that involves serving the demand located at nodes of a transportation network. The SDSS incorporates MapPointTM (cartography and network data), a database and a metaheuristic developed generate routes.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
DYNAMIC RESOURCE ALLOCATION IN ROAD TRANSPORT SECTOR USING MOBILE CLOUD COMPU...IAEME Publication
Literature review revealed application of various techniques for efficient use of existing resources in road transport sector vehicles, operators and related facilities. This issue assumes bigger dimensions in situations where there are multiple routes and the demand in the routes is highly fluctuating over the day. The application of the existing techniques as reported in literature addresses above issues to a considerable extent. However the main draw back in existing techniques is lack of
proper uninterrupted information about vehicles and demand available at a central place for allocation of vehicles in different roads and huge computational times required for processing. Cloud computing is a recently developed processing tool that is used in effective utilization of resources in transport sector under dynamic resource allocation.
A transportation scheduling management system using decision tree and iterate...IJECEIAES
This paper aimed to develop a delivery truck scheduling management system using a decision tree to support decision-making in selecting a delivery truck. First-in-first-out (FIFO) and decision tree techniques were applied to prioritize loading doors for delivery trucks with the use of iterated local search (ILS) in recommending the route for the transport of goods. Besides, an arrangement of loading doors can be assigned to the door that meets the specified conditions. The experimental results showed that the system was able to assign the job to a delivery truck under the specified conditions that were close to the actual operation at a similarity of 0.80. In addition, the application of ILS suggested the route of the food delivery truck in planning the most effective transportation route with the best total distance.
Applications of GIS in Municipal Solid Waste ManagementVignesh Sekar
Geographic Information System (GIS) is used to input, store, retrieve, manipulate, analyze and output geographically referenced data. In order to support decision making for planning and management of land use, natural resources, environment, transportation, urban facilities, and other administrative records.The Role of GIS is very large as many aspects of its planning and operations are highly dependent on spatial data & also provides a digital data bank for future monitoring program of the site…….etc
A CAR POOLING MODEL WITH CMGV AND CMGNV STOCHASTIC VEHICLE TRAVEL TIMESEditor IJMTER
Carpooling (also car-sharing, ride-sharing, lift-sharing), is the sharing of car journeys so
that more than one person travels in a car. It helps to resolve a variety of problems that continue to
plague urban areas, ranging from energy demands and traffic congestion to environmental pollution.
Most of the existing method used stochastic disturbances arising from variations in vehicle travel
times for carpooling. However it doesn’t deal with the unmet demand with uncertain demand of the
vehicle for car pooling. To deal with this the proposed system uses Chance constrained
formulation/Programming (CCP) approach of the problem with stochastic demand and travel time
parameters, under mild assumptions on the distribution of stochastic parameters; and relates it with a
robust optimization approach. Since real problem sizes can be large, it could be difficult to find
optimal solutions within a reasonable period of time. Therefore solution algorithm using tabu
heuristic solution approach is developed to solve the model. Therefore, we constructed a stochastic
carpooling model that considers the in- fluence of stochastic travel times. The model is formulated as
an integer multiple commodity network flow problem. Since real problem sizes can be large, it could
be difficult to find optimal solutions within a reasonable period of time.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using location awareness applications installed in mobile devices, data related to user mobility were collected by using crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to overcome the problem. By using this, the best transportation method can be predicted as the results of the research. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper
way to predict the traffic and recommend the best route considering the time factor and the people’s
satisfaction on various transportation methods. Therefore, in this research using location awareness
applications installed in mobile devices, data related to user mobility were collected by using
crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to
overcome the problem. By using this, the best transportation method can be predicted as the results of the
research. Therefore, people can choose what will be the best time slots & transportation methods when
planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
Applied research. Optimization of the Shuttle ServicesRAMON RIOS
Application of the queuing theory to find out the root causes of the long waiting times in the company X. The verification of the outcome was with promodel simulation software. Networking using the shortest route to optimize even better. Forecasting to predict increasing in the population and get our life cycle. Gantt chart to calculate the total days and to track the gantt chart for any delays.
Review Paper on Intelligent Traffic Control system using Computer Vision for ...JANAK TRIVEDI
In today scenario city will try to modify in the form of smart city with better facilities in terms of education, social-economic life,
better transportation availability, noise free – Eco-friendly environment availability, and ICT- Information and communication technology
enabler for development in the city. In this paper, we are reviewing different work already done or draft by some research in the field of traffic
control system – for better monitoring, tracking and managing using a computer vision system. Nowadays, most of the city installed with
C.C.T.V. – camera for monitoring the traffic related activity.
Improved Route Planning And Scheduling Of Waste Collection And Transport
GIS Oriented Service Optimization Tools For Fecal Sludge Collection-Dalower 1
1. FOSS4G Seoul, South Korea | September 14th
– 19th
, 2015
GIS ORIENTED SERVICE OPTIMIZATION TOOL FOR FECAL
SLUDGE COLLECTION
Mohammad Dalower Hossain1
, Sarawut Ninsawat2
, Shulaxan Sharma3
, Thammarat
Koottatep4
, Yuttachai Sarathai5
1
Environmental Engineering and Management (EEM) FoS, Asian Institute of Technology (AIT),
P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Email: hossain.dalower@gmail.com
2
Remote Sensing and Geographic Information Systems (RS&GIS) FoS, Asian Institute of Technology (AIT),
P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Email: sarawutn@ait.asia
3
Remote Sensing and Geographic Information Systems (RS&GIS) FoS, Asian Institute of Technology (AIT),
P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Email: shulaxan@gmail.com
4
Environmental Engineering and Management (EEM) FoS, Asian Institute of Technology (AIT),
P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Email: thamarat@ait.asia
5
Water Quality Management Bureau, Pollution Control Department,
Phahon Yothin Road, Phayathai, Bangkok 10400, Thailand
Email: s_yuttachai@hotmail.com
ABSTRACT
In developing countries most of the urban dwellers do not have access to the sewer system. People are mostly using
“on-site” systems such as septic tanks or pit latrines that need to be emptied periodically, as the densely built urban
environment will not allow new pits to be dug every time they fill up. In the conventional fecal sludge collection
systems, authorities are collecting the sludge from house to house and dump to the plant. Fecal sludge collection
system is different from the traditional vehicle routing and even from solid waste collection system in terms of dynamic
collection points, the urgency of getting the service and diversity of demand. Due to these changing conditions,
authorities are facing proper networking and management problems. This research describes algorithms that can
accommodate constraints and prioritize customers who need immediate service. The GPS log data of the fecal sludge
collection truck that maintained by Nonthaburi Municipality, Thailand has been considered as the base data during
the development of this optimization techniques. Spatial analysis has been done using Geographic Information
Systems (GIS).Tabu Search has been implemented in order to optimize. Basically, two algorithms were produced for
assisting fecal sludge collection systems. The first algorithm was able to produce multiple trips for each vehicle if
required considering all the customers having equal priority, time window. The second one was able to perform
optimizations that can accommodate priority along with the first one. The inputs to the algorithms were very simple;
distance matrix having distance between each customer and plant, customer order with latitude, longitude, order unit,
time window, priority and vehicles with capacity. Algorithms were able to produce a better result than the actual
operation or even from shortest path algorithm in term of distance. After optimization, the efficiency of the algorithms
was tested with the actual traveling distance. Travelling distances were reduced to half compared to the actual cost
and it ensured maximum utilization of vehicle capacity by allocating a maximum number of customers in each route.
2. GIS Oriented Service Optimization Tool for Fecal Sludge Collection
1. INTRODUCTION
Mostly in urban areas of developing countries, onsite sanitation systems (OSS) such as
septic tanks, pit latrines, dry toilets, and aqua privies are used for the collection of the black water
and (or) gray water where the separation of the solid and liquid fraction occurs (Strande et al.,
2014). The liquid contained in the septic tanks are drained into the sewer system, and the solid
parts are accumulated at the bottom. The solid parts that have been digested due to microbial
activities and are settled at the bottom of the septic tank are known as fecal sludge. In urban and
rural areas of the developing countries, OSS are widely used for collection and pretreatment of
excreta. Usually, the untreated fecal sludge collected from these systems are disposed haphazardly
into the urban and semi-urban environment which causes a significant threat to the environment
and the public health (Ingallinella et al., 2002). Surface and groundwater pollution, transmission
of excreta-related infections, unpleasant smell, are some of the effects in the environment and
public health. OSS is cost effective but on the other hand, there are several problems. One of the
major problems in onsite sanitation systems is emptying (Furlong et al., 2014). It cost handsome
amount of money for emptying (ICEA, 2007) as well as it is hazardous. Different small scale
emptying process have been developed but due to high cost could not sustain for the long run.
Another problem arises after emptying, where to dump and practice is simply dumped into the
immediate environment (Furlong et al., 2014). This makes the high risk of contamination of
pathogens to the environment. In larger cities, fecal sludge collection and haulage are faced with
great challenges: emptying vehicles often have no access to pits; traffic congestion prevents
efficient emptying and haulage; emptying services are poorly managed (Ingallinella et al., 2002).
Fecal Sludge Management (FSM) service chain consists of household level users, private
collection and transport (C&T) businesses that empty the fecal sludge with trucks from onsite
septic tanks and transport it to the treatment facility. This process is complicated considering the
facts regarding the distance between the customer and the service provider. Further, the service
provider also needs to offload the sludge to the plant (Dodane et al., 2012). Serving as many
customers as possible in the shortest possible time using available vehicles but optimizing travel
cost is the major concern of C&T businesses. FSM C&T system is different from traditional
logistics and solid waste collection system. In FSM, collection points are dynamic e.g. everyday
customers are different, demand is diverse and needs the services immediately.
Geographic Information Systems (GIS) is one of the most advanced technology to capture,
store, manipulate, analyze and display spatial data. GIS can be used to calculate a route in a real
scenario. One way, turn restriction, tollway should be considered in this case as a metaphor. GIS
application in waste management is mostly focused on solid waste only. GIS has been applied on
routing through selecting appropriate transfer station (Esmaili, 1972), suitable landfill sites
(Despotakis et al., 2007) and location of treatment sites (Adamides et al., 2009; Zsigraiova et al.,
2009) for solid waste management. GIS may provide significant economic and environmental
savings through the reduction of travel time, distance, fuel consumption and pollutants emissions
(Johansson, 2006; Kim et al., 2006; Sahoo et al., 2005; Tavares et al., 2008).
Vehicle Routing Problem (VRP) refers to a problem that can be defined as a set of spatially
distributed customers with associated demands that needs to be served with some vehicles having
defined capacity. In that, the starting and the ending point of the routes are predefined, and each
3. FOSS4G Seoul, South Korea | September 14th
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vehicle starts from the depot and ends at the depot. The main objective of VRP is to minimize the
traveling distance and some vehicles used (Brandão, 2004). Similar to VRP, while managing fecal
sludge collection there are a number of considerations to be made like; multiple customers, the
capacity of the septic tank to be served, multiple vehicles, vehicle capacity limit, serving time
window for customer, etc. Also, the vehicles might have to go for multiple trips if necessary.
Among the VRP algorithms Travelling Salesman Problem (TSP) is a classic combinatorial
optimization problem. In this issue, a traveling salesman is expected to visit a set of cities. The
objective of this challenge is to find the shortest tour in which the traveling salesman visits each
city once and returns to the starting city without considering vehicle capacity. To overcome the
shortcoming of TSP, Pham and Karaboga (2012) were applied Genetic Algorithms (GA), Tabu
Search (TS), Simulated Annealing (SA), and Neural Networks (NN) to a TSP consisting of 50
cities to evaluate their performances. Among these, GA was able to generate the best solution in
terms of traveling distance (5.58) followed by TS (5.68), NN (6.61) and SA (6.80). On that
particular test, Tabu Search was close to best results, but they had not evaluated the calculation
time. Bajeh and Abolarinwa (2011) compared the calculation time between Genetic Algorithm and
Tabu Search in solving the scheduling problem. They found that Tabu Search can produce better
timetables than Genetic Algorithm even at greater speed.
Hence, the requirement of effective optimization technique that can generate viable routes
that optimize the cost but without compromising the service time is always in demand. This
research is focused on the development of Tabu search based algorithm to generate an optimal
route for fecal sludge collection. The overall objective is geospatial route optimization for fecal
sludge collection in complex urban environment considering multi-path, time windows, cost
(distance) and vehicle capacity.
2. STUDY AREA AND DATA
Nonthaburi is over 400 year’s old city; it was from the time when Ayutthaya was the
capital. It is located in the northwest of Bangkok on the Chao Phraya river. It has six districts
(Figure 1) and it is a part of the greater Bangkok Metropolitan Area. The province has an area of
622.30 square kilometers, and a total population of the province is 1,334,083 as of 2010 (National
Statistics Office, Thailand). Per annum almost 9,000 cubic meters of the sludge is treated in the
fecal sludge treatment plant. The liquid fertilizers produced from sludge was tested by Kasetsart
University, Thailand and it was found safe to be used in the agriculture especially for the edible
crops (USAID, 2010).
The study was based on fecal sludge collection vehicle GPS log data obtained from the
company operated in Nonthaburi Municipality. Specifically, data between September 2013 and
February 2014 of Nonthaburi Municipality was processed for the purpose. It has been found that
four vehicles each with the capacity of six (6) cubic meters has been used for the fecal sludge
collection. Nonthaburi province was suitable due to the availability of the data and testing of the
algorithm in a real scenario. Cost was calculated regarding distance only. Traffic conditions have
not be considered due to unavailability of data. Beside the GPS log data, road network plays an
important role for the vehicle routing. Actual road network data was purchased from NOSTRA (
a business unit of ESRI (Thailand) Company Limited). GSP log data were stored in PostgreSQL
with PostGIS and pgRouting extension. PostGIS extension was required for spatial query whereas
4. GIS Oriented Service Optimization Tool for Fecal Sludge Collection
pgRouting was used for finding the distance that had been traveled by the vehicles during fecal
sludge collection. Python scripting was used for calculating the actual cost, shortest path for the
whole six months. Basic Tabu Search algorithm with time window was downloaded from GitHub
(https://github.com/pgRouting/pgrouting/tree/gsoc-vrppdtw/src/vrp_basic/src).
Figure 1. Study Area
3. METHODOLOGY
GPS log data was recorded in the geographic coordinate system i.e. WGS 1984 datum. To
calculate the distance in meter, it was necessary to project it into UTM system. QGIS was used to
convert into shapefile where the projection system was changed to UTM and later stored in
PostgreSQL with PostGIS extension. GPS log data was the combination of the way points and the
customers’ location. Hence, it was necessary to extract the customers’ location. According to the
expert interview, the distance between two septic tanks (for the different house) are more than 4
5. FOSS4G Seoul, South Korea | September 14th
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meters. So, a buffer of 2 meters was created around each GPS points. The buffer of nearby points
(if within 4 meters) overlapped with each other were merged so that all the points within that buffer
could be represented with the centroid for each overlapped buffers. Total time spent on the buffer
area was calculated from all the points within it and if the time difference between two successive
centroids was found to be ten minutes or more than that point was said to be the possible customer
location. To remove the kinematic error of the GPS, the time difference between the successive
possible customers’ was identified. If the time difference of five minutes or less was found then,
first points among the two were removed from the possible customers’ list. Finally, all the points
that lie within 50 meters from the plant location were excluded from the customer list. After
identifying the customers, it was verified with the vehicle log book. Only in 10% cases, the number
of customers’ were not matched. Finally, Python script was used for generating the customers’ list
from the GPS log data for each day for each vehicle.
Given a set of vehicles and the number of customers where the constraint being the vehicle
capacity which cannot be exceeded during serving the customers. Initially from the list of available
vehicles, all were marked as “Untapped Vehicle” as they have never been used on that day. From
the “Untapped Vehicles”, a vehicle was assigned to Tabu Search and marked as Single Used
Vehicle. From the list of customers, a distance matrix was generated in PostgreSQL using
pgRouting which indicates distance between each customer and plant. Customers order with
priority if any, distance matrix, time window and assigned vehicle was inserted in Tabu Search.
Based on distance, customer’s priority and considering time window along with the capacity of
the assigned vehicles, Tabu Search was generating optimized order of serving by that vehicle in a
single tour. After that, those customer orders were deleted from the order list. It was checked
whether there was some remaining customer or not. If there were, then it was checked whether
there were any “Untapped Vehicle” or not. In case there was any Untapped Vehicle, it was assigned
to the next tour and marked as Single Used Vehicle. Whenever there was not any, one Single Used
Vehicle was assigned for the next tour and marked that as Used Vehicle. The same process was
repeated until it serves all the customers or all vehicle became Used Vehicle. In this study, it was
considered that one vehicle can go for only two trips, one in the morning and another in the
afternoon based on the actual timing. After getting the optimal order for each tour, Dijkstra shortest
path in pgRouting was used to create routes considering turn restriction, one way, etc.
The customer order table should have columns as shown in Table 1. The first column
provides the customer ID where the first row is the details about the depot. 99999 was assigned as
the plant ID. Xcoord (longitude), Ycoord (latitude) were the geographical coordinates of the
customer location in UTM. The Demand column provides the demands that have been requested
by the customers, and the Ready_time and Due_time were used for the time windows. Ready_time
was the starting time for the time window, and Due_time was the end time. Service_time was used
for the time required to provide the service to the customers, and the Priority column described the
priority and the equal priority customers. Service time was extracted from the actual data. It varies
customer to customer based on septic tank size and time required for opening of the septic tank,
fixing the suction pipe, etc. In Priority column, 1 denoted the customers that have been left on the
previous day and need to be served on the following day whereas 0 denotes the customers that
need to be served on the same day. The starting time 0 was set to be 07:30 HRS in the morning
and the 540 would be 16:30 HRS. While serving the last customer, it was checked whether the
vehicle was able to reach the depot before closing time (16:30 HRS).
6. GIS Oriented Service Optimization Tool for Fecal Sludge Collection
Table 1. Sample customer order table
Cust_no Xcoord Ycoord Demand Ready_time Due_time Service_time Priority
99999 665126.082 1533589.780 0 0 540 0 0
124852 662428.1813 1530759.392 1500 0 360 29 0
124686 662382.3807 1535740.701 1500 0 360 25 0
124581 664704.7437 1533434.066 1500 0 360 12 1
124421 660665.2113 1534906.019 1500 0 360 27 0
The distance matrix was consisting of three columns as provided in Table 2. The first
column was the origin; the second column was the destination, and the third column was the cost
regarding traveling distance. Origin, the destination can be plant or customer. Vehicle table was
much simple one. It has only two columns as presented in Table 3. The first column as vehicle ID
and second column were the capacity in a liter.
Table 2. Sample distance matrix
To From Cost (Km)
124375 124686 4.26
124375 124421 0.34
124375 99999 6.91
124375 124852 7.41
124375 124581 6.43
124421 124581 6.28
Table 3. Sample vehicle table
V_ID Capacity
126175 6000
12618 6000
After calculating optimized route, it was compared with the actual cost and shortest path
cost by keeping the serving order as it did practically. The actual cost was the calculated from the
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GPS log data which was the actual distance traveled by each vehicle. For simplicity, all points for
each vehicle was filtered to see the route pattern. Due to the GPS error, points recorded were not
in a straight line and not also aligned properly with the road network. Before calculating actual
cost, all the GPS points were aligned with the road network.
According to the experts, the average septic tank size for a residential household in
Thailand is 1 to 2 cubic meter. Hence, with the capacity of 6 cubic meters a vehicle at a time can
serve for at the max four customers (considering the capacity of the septic tank to be 1.5 cubic
meters). After serving the customers, the vehicle needs to go back to the plant for emptying the
sludge containing in the tank. Moreover, then it had to go again for the next trip for serving the
other unserved customers. Shortest path problem is the problem of finding a path between two
vertices (or nodes) in a graph so that the sum of the weights of its edges is minimized. The inbuilt
Dijkstra algorithm from pgRouting was used for calculating the shortest path.
4. RESULT AND DISCUSSION
A total number of 1978 customers were served during the specified period, and four
vehicles were used for this purpose. The details of the customers served by each vehicle are shown
in Table 4. The available implementation of vehicle routing assumes that the customers will be
served within a single trip by each vehicle. However, simulating the available GPS log data with
the current implementation, it has been observed that all the customers could not be served with a
single trip. Hence, need to modify the implementation such that it can incorporate multiple trips
was generated and hence the existing code has been modified to facilitate the multiple trip.
Table 4. Total Number of Customers Extracted
Vehicle No. Total Customer Average Customer / day
12617 743 5
12618 406 6
12619 342 3
12829 487 5
Total Customers 1978
Taking an example of customer distribution as of December 16, 2013, total five customers’
needs to be served. The details of the attribute of the customers are shown in Figure 2, and the
distribution of the customers is shown in Figure 3. From the figure, it was clear that five customers’
were being served by one vehicle. After serving first three customers, the vehicle had to come back
to the plant to make the tank empty. The Actual cost and the shortest path cost for the particular
date were 66.08 Km and 31.41 Km respectively whereas optimized cost was found to be 27.24
Km only for the same day using one vehicle and using the multi-trip.
8. GIS Oriented Service Optimization Tool for Fecal Sludge Collection
Figure 2. Attribute of customers as of December 16, 2013
Figure 3. Customer distribution as of December 16, 2013
The optimal route was obtained using the distance matrix calculated from the actual road
network and was used in the algorithm. Two routes were generated, which were:
Plant – 124375– 124421– 124686– 124581– Plant
Plant – 124852 – Plant
The modified program was tested and verified again with some random sets of available
customer locations for some day, and the result shows that even with the multiple trips sometimes
it was difficult to serve all the customers in a single day. Here, the multiple term trips would mean
that a vehicle can go for at the maximum two trip in a day, one in the morning and one in the
afternoon. Those customers who could not be served in the ith day have to be automatically
prioritize for (i+1) th day. So, the algorithm needed further modification and enhancement such
that the priority customers would be served with higher priority the following day. This has been
implemented such that while choosing customers, the nearest priority customer from the depot was
chosen as an initial node and then subsequent nodes are chosen on the basis of the shortest distance
from the preceding node ultimately having at least one priority customer in one trip.
9. FOSS4G Seoul, South Korea | September 14th
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Taking an example of customer distribution as of September 12, 2013, total 11 customers’
needs to be served. The details of the attribute of the customers are shown in Figure 4, and the
spatial distribution of the customers is shown in Figure 5. From the figure, it is clear that 11
customers’ were being served by three vehicles. The Actual cost and the shortest path cost for the
particular date were 100.63 Km and 67.98 Km respectively whereas the cost was found to be 48.21
Km only for the same day using optimization. Here, in this example vehicle 12618, 12619 and
12617 have served seven, one and three customers respectively.
Figure 4. Attribute of customers as of September 12, 2013
Figure 5. Customer distribution as of September 12, 2013
Though, in real data there was no any priority customers, but to check whether the application
provides the optimal route or not 2534, 1784, 2011, 2226 and 1388 customers were assumed as
priority customers. All the customers have equal demands of 1,500 liters. Three vehicles with the
capacity of 6,000 liters have been assumed.
10. GIS Oriented Service Optimization Tool for Fecal Sludge Collection
The optimal route was obtained using the distance matrix calculated from the actual road network
and was used in the algorithm. Three routes were generated:
Plant – 1918 – 1784 – 1845 – 2226 – Plant for vehicle 12619
Plant – 2114 – 1680 – 1388 – 2011 – Plant for vehicle 12618
Plant – 2404 – 2479 – 2534 – Plant for vehicle 12617
Actual traveling distance, the cost calculated using shortest path and the cost using route
optimization was compared among each other to analyze the result (Figure 6). The result obtained
by comparing the datasets for 176 days implies that the optimized cost was the lowest in the
majority of days (Figure 7(a)). The accumulated total cost in the long run also supports the same
result. Moreover, the average distance traveled to serve each customer in case of route optimization
was also seen lowest among them (Figure 7(b)).
Figure 6. Comparison of cost for each day
(a) (b)
Figure 7. (a) Frequency of the best algorithm (b) Cost per customer
0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
1
7
13
19
25
31
37
43
49
55
61
67
73
79
85
91
97
103
109
115
121
127
133
139
145
151
157
163
169
175
DISTANCEINKILOMETER
DAY
Actual Cost Shortest Path Optimized Cost
14
1
161
0
20
40
60
80
100
120
140
160
180
Shortest Path Equal Optimized Cost
NUMBEROFDAYS
9.19
5.84
4.00
0
1
2
3
4
5
6
7
8
9
10
Actual Cost Shortest Path TSP Cost
DISTANCEINKILOMETER
11. FOSS4G Seoul, South Korea | September 14th
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Analyzing the number of customers, a vehicle had served per trip; it was identified that the vehicles
were optimally used in case of Tabu search based application as compared to the actual data
(Figure 8). This was the important part of optimization to maximize resource utilization. In actual
cases, there were many cases where vehicles had returned to the plant with space. They could go
to serve another customer before returned to the plant.
Figure 8. Number of customers per trip
5. CONCLUSION
A collection of fecal sludge in an urban environment is complex due to the heterogeneous road
network. A study conducted by Bill & Melinda Gates Foundation (Chowdhry and Kone, 2012)
revealed that 76% of the operating expenses for African businesses are variable costs, while in
Asia, fixed costs make up 62% of the operating costs. This fact is important as a small
improvement in the collection part can effect a significant saving in the overall cost. Therefore,
interest in the analysis of sludge collection systems arises to optimize the operation of existing
systems and to develop data and advanced techniques to design and evaluate new systems for
urban areas. Implementation of GIS approach in Nonthaburi city has shown reasonable
improvement in length of the routes. The results obtained from this study are encouraging to
expand the scope to implementing other algorithms for optimization of the routes.
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