This document discusses improving synchronization between different travel modes within transport hubs. It outlines motivation for the research, existing approaches to vehicle routing problems, and contributions of the author's new mathematical model. The author formulates the vehicle routing problem with time windows as a route-based model and solves it exactly using column generation. The goal is to minimize time costs and missed connection costs while incorporating passenger heterogeneity.
Adjusting the flow in crucial areas can maximize the overall throughput of traffic along a stretch of road. This is of particular interest in regions of high traffic density, which may be caused by high volume peak time traffic, accidents or closure of one or more lanes of the road.
34A Gaussian Plume-based Population Exposure Approach to Railroad Transportat...idescitation
Hazardous materials (hazmat) are potentially
harmful to people and environment due to their toxic
ingredients. Although a significant portion of hazmat is
transported via rail-roads, until recently the focus was on
highway shipments. In this work, we develop a risk assessment
methodology that takes into consideration the differentiating
features of trains and the characteristics of train accident.
The proposed methodology, which includes Bayes theorem
and logical diagrams, was used to study a US based case
example, which was further analyzed to gain relevant
managerial insights.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Adjusting the flow in crucial areas can maximize the overall throughput of traffic along a stretch of road. This is of particular interest in regions of high traffic density, which may be caused by high volume peak time traffic, accidents or closure of one or more lanes of the road.
34A Gaussian Plume-based Population Exposure Approach to Railroad Transportat...idescitation
Hazardous materials (hazmat) are potentially
harmful to people and environment due to their toxic
ingredients. Although a significant portion of hazmat is
transported via rail-roads, until recently the focus was on
highway shipments. In this work, we develop a risk assessment
methodology that takes into consideration the differentiating
features of trains and the characteristics of train accident.
The proposed methodology, which includes Bayes theorem
and logical diagrams, was used to study a US based case
example, which was further analyzed to gain relevant
managerial insights.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
In this presentation, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel: cost and maximizing demand coverage.
Exploring Queuing Theory to Minimize Traffic Congestion Problem in Calabar-Hi...Premier Publishers
Traffic congestion has been a serious problem that drivers are facing especially in Calabar – highway by IBB road intersection. In this paper, emphasis is placed on model formation and derivation of some parameters that will help to facilitate the flow of vehicles in this intersection to reduce traffic congestion. The channel considered in this research is multiple queue single servers. We derived variance waiting time of vehicles in the queue and in the system, expected number of vehicles in the queue and in the system waiting for service, expected waiting time of vehicles in the queue and in the system. We also determine the time each vehicle spends in the queue waiting for service and the mean queue length for all the channels in each section. The result shows fair traffic congestion in Calabar – highway by IBB road intersection especially in the morning and evening hours for all the locations.
A macroscopic traffic model based on the Markov chain process is developed for urban traffic networks. The method utilizes existing census data rather than measurements of traffic to create parameters for the model. Four versions of the model are applied to the Philadelphia regional highway network and evaluated based on their ability to predict segments of highway that possess heavy traffic.
Multi depot Time-dependent Vehicle Routing Problem with Heterogeneous FleetArian Razmi Farooji
This presentation compares two multi-objective metaheuristic algorithms, namely Simulated Annealing and Non-dominated Sorting Genetic Algorithm (NSGA II) for solving Multi depot Time-dependent Vehicle Routing Problem with Heterogeneous Fleet and was presented at Computational Multi Physics, Multi Scales
and Multi Big Data in Transport Modeling,
Simulation and Optimization (CM3) in Jyväskylä, Finland.
A Combined Method for Capacitated Periodic Vehicle Routing Problem with Stric...rahulmonikasharma
The paper develops a model for the optimal management of periodic deliveries of a given commodity with known capacity called Capacitated Periodic Vehicle Routing Problem (CPVRP). Due to the large number of customers, it is necessary to incorporate strict time windows, and pick-up and delivery in the periodic planning.. The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the the routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We model the problem as a large-scale linear mixed integer program and we propose a combined approach to solve the problem.
Solving real world delivery problem using improved max-min ant system with lo...ijaia
This paper presents a solution to real-world delive
ry problems (RWDPs) for home delivery services wher
e
a large number of roads exist in cities and the tra
ffic on the roads rapidly changes with time. The
methodology for finding the shortest-travel-time to
ur includes a hybrid meta-heuristic that combines a
nt
colony optimization (ACO) with Dijkstra’s algorithm
, a search technique that uses both real-time traff
ic
and predicted traffic, and a way to use a real-worl
d road map and measured traffic in Japan. We
previously proposed a hybrid ACO for RWDPs that use
d a MAX-MIN Ant System (MMAS) and proposed a
method to improve the search rate of MMAS. Since tr
affic on roads changes with time, the search rate i
s
important in RWDPs. In the current work, we combine
the hybrid ACO method with the improved MMAS.
Experimental results using a map of central Tokyo a
nd historical traffic data indicate that the propos
ed
method can find a better solution than conventional
methods.
The article presents different approaches to finding the optimal solution for a problem, which extends the classical traveling salesman problem. Takes into consideration the possibility of choosing a toll highway and the standard road between two cities. Describes the experimentation system. Provides mathematical model, results of the investigation, and a conclusion.
In this presentation, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel: cost and maximizing demand coverage.
Exploring Queuing Theory to Minimize Traffic Congestion Problem in Calabar-Hi...Premier Publishers
Traffic congestion has been a serious problem that drivers are facing especially in Calabar – highway by IBB road intersection. In this paper, emphasis is placed on model formation and derivation of some parameters that will help to facilitate the flow of vehicles in this intersection to reduce traffic congestion. The channel considered in this research is multiple queue single servers. We derived variance waiting time of vehicles in the queue and in the system, expected number of vehicles in the queue and in the system waiting for service, expected waiting time of vehicles in the queue and in the system. We also determine the time each vehicle spends in the queue waiting for service and the mean queue length for all the channels in each section. The result shows fair traffic congestion in Calabar – highway by IBB road intersection especially in the morning and evening hours for all the locations.
A macroscopic traffic model based on the Markov chain process is developed for urban traffic networks. The method utilizes existing census data rather than measurements of traffic to create parameters for the model. Four versions of the model are applied to the Philadelphia regional highway network and evaluated based on their ability to predict segments of highway that possess heavy traffic.
Multi depot Time-dependent Vehicle Routing Problem with Heterogeneous FleetArian Razmi Farooji
This presentation compares two multi-objective metaheuristic algorithms, namely Simulated Annealing and Non-dominated Sorting Genetic Algorithm (NSGA II) for solving Multi depot Time-dependent Vehicle Routing Problem with Heterogeneous Fleet and was presented at Computational Multi Physics, Multi Scales
and Multi Big Data in Transport Modeling,
Simulation and Optimization (CM3) in Jyväskylä, Finland.
A Combined Method for Capacitated Periodic Vehicle Routing Problem with Stric...rahulmonikasharma
The paper develops a model for the optimal management of periodic deliveries of a given commodity with known capacity called Capacitated Periodic Vehicle Routing Problem (CPVRP). Due to the large number of customers, it is necessary to incorporate strict time windows, and pick-up and delivery in the periodic planning.. The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the the routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We model the problem as a large-scale linear mixed integer program and we propose a combined approach to solve the problem.
Solving real world delivery problem using improved max-min ant system with lo...ijaia
This paper presents a solution to real-world delive
ry problems (RWDPs) for home delivery services wher
e
a large number of roads exist in cities and the tra
ffic on the roads rapidly changes with time. The
methodology for finding the shortest-travel-time to
ur includes a hybrid meta-heuristic that combines a
nt
colony optimization (ACO) with Dijkstra’s algorithm
, a search technique that uses both real-time traff
ic
and predicted traffic, and a way to use a real-worl
d road map and measured traffic in Japan. We
previously proposed a hybrid ACO for RWDPs that use
d a MAX-MIN Ant System (MMAS) and proposed a
method to improve the search rate of MMAS. Since tr
affic on roads changes with time, the search rate i
s
important in RWDPs. In the current work, we combine
the hybrid ACO method with the improved MMAS.
Experimental results using a map of central Tokyo a
nd historical traffic data indicate that the propos
ed
method can find a better solution than conventional
methods.
The article presents different approaches to finding the optimal solution for a problem, which extends the classical traveling salesman problem. Takes into consideration the possibility of choosing a toll highway and the standard road between two cities. Describes the experimentation system. Provides mathematical model, results of the investigation, and a conclusion.
Outsourcing can and does work well when done by design, via a strategy that will ensure the optimal blend of internal and external resources and capabilities. This strategy must include the appropriate governance structures to effectively manage the client demand and services provided by third parties. When done well, outsourcing can recognize and embrace the need for change. Without the analysis and forethought driven by the development of a strategy, outsourcing can be no more than short-term, tactical first aid.
SMART Infrastructure Facility Associate Research Fellow Dr Johan Barthelemy presented "Development and comparison of two interaction indices between extractive activity and groundwater resources" as part of the SMART Seminar Series on Tuesday, 21 July 2015.
Similar to SMART Seminar Series: Improving Public Transport Accessibility via the Optimisation and Synchronisation of Schedules for Key Transport Modes
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...BRTCoE
Camila Balbontin is a Postgraduate Research Fellow at the Institute of Transport and Logistics Studies (ITLS) of University of Sydney. In February 2018, she completed her PhD under the supervision of Professor David Hensher where she focused on integrating decision heuristics and behavioural refinements into travel choice models. She was awarded the ITLS prize for Research Excellence in Transport or Logistics 2017. Camila also holds a bachelor degree in the field of Civil Engineering with a diploma in Industrial Engineering and in Transportation and Logistics from Pontificia Universidad Católica de Chile. She did her MSc degree at the same university under the supervision of Professor Juan de Dios Ortúzar. Her MSc thesis estimated the valuation of households and neighbourhood attributes in the centre of Santiago.
As a Postgraduate Research Fellow, her main focus is choice modelling and travel behaviour. She is currently working on projects related to the BRT Centre of Excellence, business location decisions, hybrid modelling, value uplift, among others.
Working Paper - http://sydney.edu.au/business/itls/research/publications/working_papers
How can we make traffic flow better so fewer of us are sitting in traffic jams for shorter periods of time – if at all?
Researcher Lina Kattan looks at Intelligent Traffic Systems that optimize the operation, safety and costs of a city’s transportation network through sustainable traffic control and transportation management strategies. These systems are designed to manage traffic congestion, signal controls and prediction of bus and LRT arrivals.
Read on to learn about solutions that are working and how new developments will change the traffic jigsaw in the not-to-distant future.
You can also see the full webinar recording at: http://www.ucalgary.ca/explore/can-we-make-traffic-jams-obsolete
A Minimum Spanning Tree Approach of Solving a Transportation Probleminventionjournals
: This work centered on the transportation problem in the shipment of cable troughs for an underground cable installation from three supply ends to four locations at a construction site where they are needed; in which case, we sought to minimize the cost of shipment. The problem was modeled into a bipartite network representation and solved using the Kruskal method of minimum spanning tree; after which the solution was confirmed with TORA Optimization software version 2.00. The result showed that the cost obtained in shipping the cable troughs under the application of the method, which was AED 2,022,000 (in the United Arab Emirate Dollar), was more effective than that obtained from mere heuristics when compared.
My first presentation as a PhD student in which I outline the background to my research project. This presentation was given as part of the University of Southampton Transportation Research Group seminar programme.
A Minimum Spanning Tree Approach of Solving a Transportation Probleminventionjournals
: This work centered on the transportation problem in the shipment of cable troughs for an underground cable installation from three supply ends to four locations at a construction site where they are needed; in which case, we sought to minimize the cost of shipment. The problem was modeled into a bipartite network representation and solved using the Kruskal method of minimum spanning tree; after which the solution was confirmed with TORA Optimization software version 2.00. The result showed that the cost obtained in shipping the cable troughs under the application of the method, which was AED 2,022,000 (in the United Arab Emirate Dollar), was more effective than that obtained from mere heuristics when compared
PROUDCTION AND OPERATION MANAGEMENT.pptxSouvik Das
- Assessed research papers to evaluate the most apt model used by FedEX for optimum Airline cargo dynamic logistic algorithms - Operations research LPP with aircraft regression equations and incidence matrix for obtaining the most optimum cargo routes
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Similar to SMART Seminar Series: Improving Public Transport Accessibility via the Optimisation and Synchronisation of Schedules for Key Transport Modes (20)
Richard Skarbez presented a seminar titled "Cognitive Illusions in Virtual Reality: What do I mean? And why should you care?" as part of the SMART Seminar Series on the 4th March 2019.
More information:
https://news.eis.uow.edu.au/event/cognitive-illusions-in-virtual-reality-what-do-i-mean-and-why-should-you-care/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility
Dr Ricardo Peculis presented a seminar titled "Trusted Autonomous Systems as System of Systems" as part of the SMART Seminar Series on 19th February 2019.
More information:
https://news.eis.uow.edu.au/event/trusted-autonomous-systems-as-system-of-systems/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility"
David Kennewell presented a seminar titled " "The Evolution of the Metric System: From Precious Lumps of Metal to Constants of Nature" as part of the SMART Seminar Series on 1st November 2018.
More information:
https://news.eis.uow.edu.au/event/the-evolution-of-the-metric-system-from-precious-lumps-of-metal-to-constants-of-nature/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility"
Dr Ilya Budovsky presented a seminar titled "The Evolution of the Metric System: From Precious Lumps of Metal to Constants of Nature" as part of the SMART Seminar Series on 1st November 2018.
More information:
https://news.eis.uow.edu.au/event/the-evolution-of-the-metric-system-from-precious-lumps-of-metal-to-constants-of-nature/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Johan Barthelemy presented a seminar titled "Using AI and edge computing devices for traffic flow monitoring" as part of the SMART Seminar Series on 11th October 2018.
More information: https://news.eis.uow.edu.au/event/using-ai-and-edge-computing-devices-for-traffic-flow-monitoring/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Prof Willy Susilo presented a seminar titled "Blockchain and its Applications" as part of the SMART Seminar Series on 20th September 2018.
More information: https://news.eis.uow.edu.au/event/blockchain-and-its-applications/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Prof Theirry Monteil & Fabian Ho presented a seminar titled "From an IoT cloud based architecture to Edge for dynamic service" as part of the SMART Seminar Series on 24th August 2018.
More information: https://news.eis.uow.edu.au/event/from-an-iot-cloud-based-architecture-to-edge-for-dynamic-service/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Bobby Du and Paul-Antonin Dublanche presented a seminar titled "Is bus bunching serious in Sydney? Preliminary findings based on Opal card data analysis" as part of the SMART Seminar Series on 2nd August 2018.
More information: https://news.eis.uow.edu.au/event/is-bus-bunching-serious-in-sydney-preliminary-findings-based-on-opal-card-data-analysis/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Nicolas Verstaevel presented a seminar titled "Keep it SMART, keep it simple! – Challenging complexity with self-organising software" as part of the SMART Seminar Series on 24th July 2018.
More information: https://news.eis.uow.edu.au/event/keep-it-smart-keep-it-simple-challenging-complexity-with-self-organising-software/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Boulent Imam presented a seminar titled "Risk-based bridge assessment under changing load-demand and environmental conditions" as part of the SMART Seminar Series on 17th July 2018.
More information: https://news.eis.uow.edu.au/event/risk-based-bridge-assessment-under-changing-load-demand-and-environmental-conditions/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Rohan Wickramasuriya presented a seminar titled "Deep Learning: Fundamentals and Practice" as part of the SMART Seminar Series on 29th May 2018.
More information: http://www.uoweis.co/event/deep-learning-fundamentals-and-practice/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Sarah Dunn presented a seminar titled "Infrastructure Resilience: Planning for Future Extreme Events" as part of the SMART Seminar Series on 12th April 2018.
More information: http://www.uoweis.co/event/infrastructure-resilience-planning-for-future-extreme-events/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr George Grozev presented a seminar titled "Potential use of drones for infrastructure inspection and survey: as part of the SMART Seminar Series on 27th March 2018.
More information: http://www.uoweis.co/event/potential-use-of-drones-for-infrastructure-inspection-and-survey/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Professor Timoteo Carletti presented a seminar titled "A journey in the zoo of Turing patterns: the topology does matter as part of the SMART Seminar Series on 8th March 2018.
More information: http://www.uoweis.co/event/a-journey-in-the-zoo-of-turing-patterns-the-topology-does-matter/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Dr Carole Adam presented a seminar titled Human behaviour modelling and simulation for crisis management as part of the SMART Seminar Series on 1st March 2018.
More information: http://www.uoweis.co/event/human-behaviour-modelling-and-simulation-for-crisis-management/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Professor Graham Harris presented a seminar titled Dealing with uncertainty: With the observer in the loop as part of the SMART Seminar Series on 13th February 2018.
More information: http://www.uoweis.co/event/dealing-with-uncertainty-with-the-observer-in-the-loop/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Senior Professor Pascal Perez presented on Smart Cities; The Good, The Bad & The Ugly as part of the SMART Seminar Series on 30th January 2018.
More information: http://www.uoweis.co/event/smart-cities-the-good-the-bad-the-ugly/
Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/
Visiting PhD student, Morgane Dumont presented on how to improve the order of evolutionary models in agent-based simulations for population dynamics as part of the SMART Seminar Series on 15 December 2017.
More information: http://www.uoweis.co/event/how-to-improve-the-order-of-evolutionary-models-in-agent-based-simulations-for-population-dynamics/
Keep updated with future events: http://www.uoweis.co/tag/smart-infrastructure/
Professor Tierry Monteil, professor in computer science at INSA – University of Toulouse and researcher at LAAS-CNRS presented on OneM2M and the interoperatbility of the IoT as part of the SMART Seminar Series on 13 December 2017.
More information: http://www.uoweis.co/event/onem2m-towards-end-to-end-interoperability-of-the-iot/
Keep updated with future events: http://www.uoweis.co/tag/smart-infrastructure/
Professor Peter Bridgewater, Chair of Landcare ACT and Adjunct Professor in Terrestrial and Marine Biodiversity Governance at the University of Canberra, presented on blue-green vs grey-black infrastructure and which is the best way forward, as part of the SMART Seminar Series on 24 November 2017.
More information: http://www.uoweis.co/event/blue-green-vs-grey-black-infrastructure-which-is-best-for-c21st-survival/
Keep updated with future events: http://www.uoweis.co/tag/smart-infrastructure/
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
SMART Seminar Series: Improving Public Transport Accessibility via the Optimisation and Synchronisation of Schedules for Key Transport Modes
1. Synchronisation of Key Travel Modes
within a Transport Hub
Dr Michelle Dunbar
SMART Infrastucture Facility,
University of Wollongong
May 26, 2015
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 1/35
2. Outline
Motivation for improving synchronisation in multi-modal transport.
Variations of the Vehicle Routing Problem (VRP).
A mathematical formulation for the VRPTW with heterogeneous
travellers.
Preliminary results.
Future directions + Application.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 2/35
3. Motivation for Improved Synchronisation
In modern cities, transport infrastructure has typically developed according to a radial
pattern, in response to urban-sprawl.
Figure: Heatmap of population density in Sydney. Source: RP Data.
Population density increase may lead to inaccessibility to transportation services.
Infrastructure has traditionally developed separately and sequentially =⇒ lack of
complementarity and synchronisation between services at Hubs (△).
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 3/35
4. Motivation for Improved Synchronisation
Passengers increasingly required to
make a number of interchanges at
Hubs, between different transport
modes.
Excessive waiting-times, infrequent
feeder services =⇒ poor connectivity.
Long-term planning and coordination: A
key driver for environmentally and
financially sustainable transport
development (Transport for NSW, 2012).
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 4/35
5. Motivation for Improved Synchronisation
In areas without an existing transport infrastructure (such as an existing rail line),
buses are typically used to service the population.
- May be undesirable: fixed routes, infrequent services =⇒ increased car usage.
One approach commonly used around the
world, is that of a Dial-a-Ride shuttle-bus
system. (e.g. SkyBus in Melbourne)
Mobile technology has allowed for ease-of-use
and uptake for services to major Transport
Hubs.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 5/35
6. The Vehicle Routing Problem
The Vehicle Routing Problem: Visit each node exactly once in minimal time.
Source: http://neo.lcc.uma.es/dynamic/vrp.html
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 6/35
7. Existing Vehicle Routing Approaches
Vehicle Routing Problem (VRP), VRPTW (Vehicle Routing with Time Windows) and
DARP (Dial-a-Ride Problems).
1 Typically assume passengers/items are homogeneous w.r.t importance/priority,
2 Minimise total route time, cost or number of vehicles,
3 Solution approaches have typically utilised a combination of exact and heuristic
techniques (eg. tabu search),
4 Ignore the potential multi-modal aspect of a passenger’s trip.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 7/35
8. Existing Vehicle Routing Approaches
Recent extensions include:
1 Multi-zone, multi-trip VRPTW to and from a
one or more depots (Crainic et al., 2012).
2 Heterogeneity of items and route-cost factors:
weight, volume, distance and number of stops.
(Cesseli et al., 2009.)
3 Exact solution techniques: Column generation.
(Ceselli et al., 2009)
4 Customer perceptions of quality of service:
waiting time at pick up node, trip length.
(Pacquette et al., 2013).
Figure 1: Example of a multi-zone, multi-trip solution.
vs
Figure 2: Non-Perishable vs Perishable items.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 8/35
9. Contributions of Our Model
We extend the ideas of Ceselli et al. and Pacquette et al. Our approach:
1 Incorporates passenger heterogeneity with respect to value-of-time and importance of
outbound connection,
2 Minimises the time cost and missed connection cost,
3 Solved exactly via Column Generation.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 9/35
10. Route-Based Formulation for the VRPTW
The VRPTW model may be formulated as a route-based model.
- Each route corresponds to a column of the coefficient matrix and has an
associated decision variable.
xr =
1, If route r is chosen,
0, otherwise.
(1)
Example:
1
0
1
,
0
1
0
Passenger 1
Passenger 2
Passenger 3
Route 1 Route 2
s t1
2
3
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 10/35
11. Route-Based Formulation for the VRPTW
The VRPTW model may be formulated as a route-based model.
- Each route corresponds to a column of the coefficient matrix and has an
associated decision variable.
xr =
1, If route r is chosen,
0, otherwise.
(1)
Example:
1
0
1
,
0
1
0
Passenger 1
Passenger 2
Passenger 3
Route 1 Route 2
s t1
2
3x1 x2
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 10/35
12. Route-Based Formulation for the VRPTW
The VRPTW model may be formulated as a route-based model.
- Each route corresponds to a column of the coefficient matrix and has an
associated decision variable.
xr =
1, If route r is chosen,
0, otherwise.
(1)
Example:
1
0
1
,
0
1
0
Passenger 1
Passenger 2
Passenger 3
Route 1 Route 2
s t1
2
3x1 x2
s 1
3
t
Route 1
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 10/35
13. Route-Based Formulation for the VRPTW
The VRPTW model may be formulated as a route-based model.
- Each route corresponds to a column of the coefficient matrix and has an
associated decision variable.
xr =
1, If route r is chosen,
0, otherwise.
(1)
Example:
1
0
1
,
0
1
0
Passenger 1
Passenger 2
Passenger 3
Route 1 Route 2
s t1
2
3x1 x2
s
2
t
Route 2
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 10/35
20. Solving the VRPTW using Column Generation
Objective is to obtain a minimal time-cost assignment of available vehicles to
passenger pick-ups, ensuring each passenger is picked up within their specified
time-window.
Master Problem
Minimise :
r∈R
crxr
Subject to :
r∈R
airxr = 1 ∀i ∈ N
r∈R
xr ≤ N, xr ∈ {0, 1}
Subproblem
Generate a feasible vehicle
route (satisfying time window
and duration constraints).
Append to the set:
R = set of all possible routes.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 12/35
21. Route-Based VRPTW with Passenger Heterogeneity
Objective is minimise both time cost and missed (outbound) connection cost
at the Transport Hub, whilst ensuring each passenger is picked up within their
specified time window.
Master Problem
Minimise :
r∈R
cr + λcM
r xr
Subject to :
r∈R
airxr = 1 ∀i ∈ N
r∈R
xr ≤ N, xr ∈ {0, 1}
Subproblem
Generate a feasible vehicle
route (satisfying time window
and duration constraints).
Append to the set:
R = set of all possible routes.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 13/35
22. Subproblem
A Label-Setting algorithm is used to determine the path with minimal reduced cost:
- Let π denote a path from source to sink.
- Let ti be the time-cost incurred by travelling from the predecessor node π−(i) to node i.
- Let wi be the dual multiplier for node i.
- Let li and ui denote the lower and upper bounds of the time window for node i.
Subproblem Formulation
Minimise : λcM
r +
i∈π
(ti − wi)
Subject to: li ≤
i∈π(i)
ti ≤ ui, ∀i ∈ N.
i∈π
ti ≤ Tmax, ∀i ∈ N
π is a path from s to t.
Where: cr = i∈π ti, Time Cost
cM
r = i∈π max{pi(cr−di),0}, MC.Cost.
s t
1
2
3
4
5
6
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 14/35
23. Subproblem
A Label-Setting algorithm is used to determine the path with minimal reduced cost:
- Let π denote a path from source to sink.
- Let ti be the time-cost incurred by travelling from the predecessor node π−(i) to node i.
- Let wi be the dual multiplier for node i.
- Let li and ui denote the lower and upper bounds of the time window for node i.
Subproblem Formulation
Minimise : λcM
r +
i∈π
(ti − wi)
Subject to: li ≤
i∈π(i)
ti ≤ ui, ∀i ∈ N.
i∈π
ti ≤ Tmax, ∀i ∈ N
π is a path from s to t.
Where: cr = i∈π ti, Time Cost
cM
r = i∈π max{pi(cr−di),0}, MC.Cost.
s t
1
2
3
4
5
6s
1
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 14/35
24. Subproblem
A Label-Setting algorithm is used to determine the path with minimal reduced cost:
- Let π denote a path from source to sink.
- Let ti be the time-cost incurred by travelling from the predecessor node π−(i) to node i.
- Let wi be the dual multiplier for node i.
- Let li and ui denote the lower and upper bounds of the time window for node i.
Subproblem Formulation
Minimise : λcM
r +
i∈π
(ti − wi)
Subject to: li ≤
i∈π(i)
ti ≤ ui, ∀i ∈ N.
i∈π
ti ≤ Tmax, ∀i ∈ N
π is a path from s to t.
Where: cr = i∈π ti, Time Cost
cM
r = i∈π max{pi(cr−di),0}, MC.Cost.
s t
1
2
3
4
5
6s
1
2
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 14/35
25. Subproblem
A Label-Setting algorithm is used to determine the path with minimal reduced cost:
- Let π denote a path from source to sink.
- Let ti be the time-cost incurred by travelling from the predecessor node π−(i) to node i.
- Let wi be the dual multiplier for node i.
- Let li and ui denote the lower and upper bounds of the time window for node i.
Subproblem Formulation
Minimise : λcM
r +
i∈π
(ti − wi)
Subject to: li ≤
i∈π(i)
ti ≤ ui, ∀i ∈ N.
i∈π
ti ≤ Tmax, ∀i ∈ N
π is a path from s to t.
Where: cr = i∈π ti, Time Cost
cM
r = i∈π max{pi(cr−di),0}, MC.Cost.
s t
1
2
3
4
5
6s
1
2
4
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 14/35
26. Subproblem
A Label-Setting algorithm is used to determine the path with minimal reduced cost:
- Let π denote a path from source to sink.
- Let ti be the time-cost incurred by travelling from the predecessor node π−(i) to node i.
- Let wi be the dual multiplier for node i.
- Let li and ui denote the lower and upper bounds of the time window for node i.
Subproblem Formulation
Minimise : λcM
r +
i∈π
(ti − wi)
Subject to: li ≤
i∈π(i)
ti ≤ ui, ∀i ∈ N.
i∈π
ti ≤ Tmax, ∀i ∈ N
π is a path from s to t.
Where: cr = i∈π ti, Time Cost
cM
r = i∈π max{pi(cr−di),0}, MC.Cost.
s t
1
2
3
4
5
6s
1
2
4
6
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 14/35
27. Subproblem
A Label-Setting algorithm is used to determine the path with minimal reduced cost:
- Let π denote a path from source to sink.
- Let ti be the time-cost incurred by travelling from the predecessor node π−(i) to node i.
- Let wi be the dual multiplier for node i.
- Let li and ui denote the lower and upper bounds of the time window for node i.
Subproblem Formulation
Minimise : λcM
r +
i∈π
(ti − wi)
Subject to: li ≤
i∈π(i)
ti ≤ ui, ∀i ∈ N.
i∈π
ti ≤ Tmax, ∀i ∈ N
π is a path from s to t.
Where: cr = i∈π ti, Time Cost
cM
r = i∈π max{pi(cr−di),0}, MC.Cost.
s t
1
2
3
4
5
6s
1
2
4
6 t
1
1
0
1
0
1
Route Cost = cr + λcM
r
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 14/35
28. Preliminary Numerical Results
We randomly generated 4 different datasets with characteristics reflecting ‘likely’
passenger compositions according to time-of-day requests.
- School commute (≈ 8am/3pm),
- Balanced number of requests (≈ 11am/2pm),
- Inter-city commute (≈ 7am/5pm),
- Business commute (≈ 6am/6pm).
For each of these datasets, we simulated 10 random instances with different passenger
outbound connection departure times at the Hub, to determine the effectiveness of our
algorithm.
Each dataset consists of 30 passengers, with the restriction that vehicles must return to
the Hub in <= 20 mins.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 15/35
29. Preliminary Numerical Results
In the slides that follow, we compare:
- The Base Case (Min TTT): Objective is to minimise Total Travel Time (TTT).
- Our Model (Min TTT+MC): Objective is to minimise Total Travel Time and Missed
Connection Cost.
We compare the following quantities:
- Time Cost,
- Missed Connection Cost,
- Time Cost + Missed Connection Cost (weighted),
- Total Cost (includes additional vehicle cost ($40/20 min), if required).
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 16/35
30. Results: School (5,5,15,5)
−5 −4 −3 −2 −1 0 1 2 3 4 5
−5
−4
−3
−2
−1
0
1
2
3
4
5
Distance (kms)
Distance(kms)
Plot of the Vehicle Routing Solution
(Obj: Minimise Total Travel Time): Using 6 vehicles.
1
2
3
10
21
25
5
14
16
18
23
30
6
7
8
22
24
27
28
29
4
13
15
19
9
11
17
26
1220
Total Travel Time Cost = 89,
Missed Connections = 4,
Missed Connection Cost = 310,
Weighted Cost Sum = 244.
Hub Aircraft Connection: 5 Inter−city Train Connection: 5 Bus Connection: 15 Walk Connection: 5
−5 −4 −3 −2 −1 0 1 2 3 4 5
−5
−4
−3
−2
−1
0
1
2
3
4
5
Distance (kms)
Distance(kms)
Plot of the Vehicle Routing Solution
(Obj: Minimise Total Travel Time and Missed Connection Cost): Using 6 vehicles.
9
11
17
6
7
8
22
24
27
28
29
2
3
10
21
23
30
1
4
13
15
19
1220
25
5
14
16
18
26
Total Travel Time Cost = 90,
Missed Connections = 0,
Missed Connection Cost = 0,
Weighted Cost Sum = 90.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 17/35
33. Results: Business (15,10,5,0)
−5 −4 −3 −2 −1 0 1 2 3 4 5
−5
−4
−3
−2
−1
0
1
2
3
4
5
Distance (kms)
Distance(kms)
Plot of the Vehicle Routing Solution
(Obj: Minimise Total Travel Time): Using 6 vehicles.
1
6
10
22
27
8
16 18
21
29
5
13
23
24
25
3
9
12
17
19
2
4 14
15
28
7
1120
26
30
Total Travel Time Cost = 88,
Missed Connections = 3,
Missed Connection Cost = 320,
Weighted Cost Sum = 248.
Hub Aircraft Connection: 15 Inter−city Train Connection: 10 Bus Connection: 5
−5 −4 −3 −2 −1 0 1 2 3 4 5
−5
−4
−3
−2
−1
0
1
2
3
4
5
Distance (kms)
Distance(kms)
Plot of the Vehicle Routing Solution
(Obj: Minimise Total Travel Time and Missed Connection Cost): Using 8 vehicles.
1
6
26
810
22
27
2
4 14
18
29
3
15
21
28
5
13
23
24
25
1120
30
9
12
17
19
7
16
Total Travel Time Cost = 90,
Missed Connections = 0,
Missed Connection Cost = 0,
Weighted Cost Sum = 90(170).
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 20/35
34. Average Costs for each Dataset over 10 Random Instances
Dataset
TotalCost($)
A Comparison of the Average Total Costs between Min TTT and Min TTT+MC over 10 Instances for each Dataset
School Balanced Inter−City Business
0
50
100
150
200
250
300
350
400
450
Time Cost (Min. TTT)
Missed Connection Cost (Min. TTT)
Additional Vehicle/Driver Cost (Min. TTT)
Time Cost (Min. TTT+MC)
Missed Connection Cost (Min. TTT+MC)
Additional Vehicle/Driver Cost (Min. TTT+MC)
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 21/35
35. Results: Average Percentage Improvement
Average percentage improvement of Min TTT+MC over the Min TTT approach.
Travel Cost MC Cost Weighted Sum Total Cost
School -1.35 100.00 55.67 55.67
Balanced -11.16 94.75 59.38 45.40
Inter-City -8.49 100.00 57.10 36.87
Business -6.705 95.41 73.76 57.37
Average -6.93 97.54 61.48 48.83
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 22/35
36. Remarks and Conclusions
Using the same number of vehicles, it is possible to obtain a route with a 100%
decrease in missed connection cost, for only a 1.3% increase in time cost.
Over all 4 dataset types, the average reduction in missed connection cost was
between 94 − 100%.
Over all 4 dataset types, the Min TTT+MC approach outperformed the Min TTT
approach, even when (≤ 2) additional vehicles costs are accounted for, by an
average of 48.83%
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 23/35
37. Future Directions
Inclusion of additional passenger-centric measures.
Application to perishable-good delivery problem (eg. just-in-time delivery).
Figure: Routes for the delivery of spare parts from CP to Drop-points for Sydney Network.
Incorporation of real-time (offline) traffic data for specific time-of-day.
Extend to include delay information.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 24/35
38. Application to Vehicle Logistics Company: DropPoint
How to reduce distribution time from CP → DPs?
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 25/35
39. Application to Vehicle Logistics Company: DropPoint
Sydney Network.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 26/35
40. Application to Vehicle Logistics Company: DropPoint
Subproblem: Minimise reduced-cost, subject to:
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 27/35
41. Application to Vehicle Logistics Company: DropPoint
Incorporate a variable link travel-time reflecting time-of-day information.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 28/35
42. Application to Vehicle Logistics Company: DropPoint
A step-function approximation for given data granularity.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 29/35
43. Application to Vehicle Logistics Company: DropPoint
How does our model know which time-of-day dataset to use?
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 30/35
44. Application to Vehicle Logistics Company: DropPoint
We use a linearised model of a Heaviside step function.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 31/35
45. Application to Vehicle Logistics Company: DropPoint
For example, if the current time is 1 : 30pm, but have discretisations of 1
hour:
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 32/35
46. Application to Vehicle Logistics Company: DropPoint
This results in:
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 33/35
47. Application to Vehicle Logistics Company: DropPoint
This will be used to select the correct travel-time across a link, on-the-fly.
Michelle Dunbar, UoW Synchronisation ofTravel Modes within a Transport Hub 34/35