This presentation is made to represent the basic transportation model. The aim of this presentation is to implement the transportation model in solving transportation problem.
The assignment problem is a special case of transportation problem in which the objective is to assign ‘m’ jobs or workers to ‘n’ machines such that the cost incurred is minimized.
The transportation problem is a special type of linear programming problem where the objective is to minimize the cost of distributing a product from a number of sources or origins to a number of destinations.
Because of its special structure, the usual simplex method is not suitable for solving transportation problems. These problems require a special method of solution.
The assignment problem is a special case of transportation problem in which the objective is to assign ‘m’ jobs or workers to ‘n’ machines such that the cost incurred is minimized.
The transportation problem is a special type of linear programming problem where the objective is to minimize the cost of distributing a product from a number of sources or origins to a number of destinations.
Because of its special structure, the usual simplex method is not suitable for solving transportation problems. These problems require a special method of solution.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
2. Aim of Transportation Model
To find out optimum transportation
schedule keeping in mind cost of
transportation to be minimized.
3. What is a Transportation Problem?
• The transportation problem is a special type of
LPP where the objective is to minimize the cost
of distributing a product from a number of
sources or origins to a number of destinations.
• Because of its special structure the usual simplex
method is not suitable for solving transportation
problems. These problems require special
method of solution.
4. The Transportation Problem
• The problem of finding the minimum-cost
distribution of a given commodity
from a group of supply centers (sources) i=1,…,m
to a group of receiving centers (destinations)
j=1,…,n
• Each source has a certain supply (si)
• Each destination has a certain demand (dj)
• The cost of shipping from a source to a
destination is directly proportional to the
number of units shipped
6. The Transportation Model
Characteristic
• A product is to be transported from a number of sources
to a number of destinations at the minimum possible
cost.
• Each source is able to supply a fixed number of units of
the product, and each destination has a fixed demand for
the product.
• The linear programming model has constraints for supply
at each source and demand at each destination.
• All constraints are equalities in a balanced transportation
model where supply equals demand.
• Constraints contain inequalities in unbalanced models
where supply is not equal to demand.
7. Application of Transportation Model
Minimize shipping costs
Determine low cost location
Find minimum cost production schedule
Military distribution system
8. Two Types of Transportation
Problem
• Balanced Transportation Problem
where the total supply equals total demand
• Unbalanced Transportation Problem
where the total supply is not equal to the
total demand
9. Phases of Solution of
Transportation Problem
• Phase I- obtains the initial basic feasible
solution
• Phase II-obtains the optimal basic solution
10. Initial Basic Feasible Solution
North West Corner Rule (NWCR)
Row Minima Method
Column Minima Method
Least Cost Method
Vogle Approximation Method (VAM)
11. Northwest corner rule
• The northwest-corner rule requires that we start in
the upper left-hand cell (or northwest corner) of the
table and allocate units to shipping routes as follows:
• 1. Exhaust the supply (factory capacity) of each row
before moving down to the next row.
• 2. Exhaust the (warehouse) requirements of each
column before moving to the next column on the
right.
• 3. Check to ensure that all supplies and demands are
met.
12. Least cost method
• The intuitive method makes initial allocations based on
lowest cost. This straightforward approach uses the
following steps:
• 1. Identify the cell with the lowest cost. Break any ties for
the lowest cost arbitrarily.
• 2. Allocate as many units as possible to that cell without
exceeding the supply or demand. Then cross out that row
or column (or both) that is exhausted by this assignment.
• 3. Find the cell with the lowest cost from the remaining
(not crossed out) cells.
• 4. Repeat steps 2 and 3 until all units have been allocated.
13. Vogel’s approximation method
• This method also takes costs into account in allocation. Five
steps are involved in applying this heuristic:
• Step 1: Determine the difference between the lowest two cells
in all rows and columns, including dummies.
• Step 2: Identify the row or column with the largest difference.
Ties may be broken arbitrarily.
• Step 3: Allocate as much as possible to the lowest-cost cell in
the row or column with the highest difference. If two or more
differences are equal, allocate as much as possible to the
lowest-cost cell in these rows or columns.
14. Step 4: Stop the process if all row and column requirements
are met. If not, go to the next step.
Step 5: Recalculate the differences between the two lowest
cells remaining in all rows and columns. Any row and
column with zero supply or demand should not be used in
calculating further differences. Then go to Step 2.
The Vogel's approximation method (VAM) usually produces
an optimal or near- optimal starting solution. One study
found that VAM yields an optimum solution in 80 percent of
the sample problems tested.
16. Optimum Basic Solution:
Stepping-Stone Method
1. Select any unused square to evaluate
2. Beginning at this square, trace a closed
path back to the original square via
squares that are currently being used
3. Beginning with a plus (+) sign at the
unused corner, place alternate minus and
plus signs at each corner of the path just
traced
17. Stepping-Stone Method
4. Calculate an improvement index by first
adding the unit-cost figures found in each
square containing a plus sign and subtracting
the unit costs in each square containing a
minus sign
5. Repeat steps 1 though 4 until you have
calculated an improvement index for all
unused squares. If all indices are ≥ 0, you
have reached an optimal solution.
19. Initial Feasible Solution using
Northwest Corner Rule
FROM
TO A.
ALBUQUERQU
E
B.
BOSTON
C.
CLEVELAND
FACTORY
CAPACITY
D. DES
MOINES 5 4
3
100
E. EVANSVILLE
8 4
3
300
F. FORT
LAUDERDALE 9 7
5
300
WAREHOUSE
DEMAND 300 200 200 700
100
200 100
100 200
IFS= DA + EA +EB + FB + FC = 100(5) + 200(8) + 100(4) + 100(7) + 200(5)
= 500 + 1600 + 400 + 700 + 1000 = 4200
20. Rs5
Rs8 Rs4
Rs4
+ -
+-
Optimizing Solution using
Stepping-Stone Method
To (A)
Albuquerque
(B)
Boston
(C)
Cleveland
(D) Des Moines
(E) Evansville
(F) Fort Lauderdale
Warehouse
requirement 300 200 200
Factory
capacity
300
300
100
700
Rs5
Rs5
Rs4
Rs4
Rs3
Rs3
$9
Rs8
$7
From
100
100
100
200
200
+-
-+
1
100
201 99
99
100200Figure C.5
Des Moines-
Boston index
= Rs4 – Rs5 + Rs8 - Rs4
= Rs3
21. Stepping-Stone Method
To (A)
Albuquerque
(B)
Boston
(C)
Cleveland
(D) Des Moines
(E) Evansville
(F) Fort Lauderdale
Warehouse
requirement 300 200 200
Factory
capacity
300
300
100
700
Rs5
Rs5
Rs4
Rs4
Rs3
Rs3
Rs9
Rs8
Rs7
From
100
100
100
200
200
Figure C.6
Start
+-
+
-+
-
Des Moines-Cleveland index
= Rs3 - Rs5 + Rs8 - Rs4 + Rs7 - Rs5 = Rs4
22. Stepping-Stone Method
To (A)
Albuquerque
(B)
Boston
(C)
Cleveland
(D) Des Moines
(E) Evansville
(F) Fort Lauderdale
Warehouse
requirement 300 200 200
Factory
capacity
300
300
100
700
Rs5
Rs5
Rs4
Rs4
Rs3
Rs3
Rs9
Rs8
Rs7
From
100
100
100
200
200
Evansville-Cleveland index
= Rs3 - Rs4 + Rs7 - Rs5 = Rs1
(Closed path = EC - EB + FB - FC)
Fort Lauderdale-Albuquerque index
= Rs9- Rs7 + Rs4 - Rs8 = -Rs1
(Closed path = FA - FB + EB - EA)
23. Stepping-Stone Method
1. If an improvement is possible, choose the
route (unused square) with the largest
negative improvement index
2. On the closed path for that route, select the
smallest number found in the squares
containing minus signs
3. Add this number to all squares on the closed
path with plus signs and subtract it from all
squares with a minus sign
24. Stepping-Stone Method
To (A)
Albuquerque
(B)
Boston
(C)
Cleveland
(D) Des Moines
(E) Evansville
(F) Fort Lauderdale
Warehouse
requirement 300 200 200
Factory
capacity
300
300
100
700
Rs5
Rs5
Rs4
Rs4
Rs3
Rs3
Rs9
Rs8
Rs7
From
100
100
100
200
200
Figure C.7
+
+-
-
1. Add 100 units on route FA
2. Subtract 100 from routes FB
3. Add 100 to route EB
4. Subtract 100 from route EA
25. Stepping-Stone Method
To (A)
Albuquerque
(B)
Boston
(C)
Cleveland
(D) Des Moines
(E) Evansville
(F) Fort Lauderdale
Warehouse
requirement 300 200 200
Factory
capacity
300
300
100
700
Rs5
Rs5
Rs4
Rs4
Rs3
Rs3
Rs9
Rs8
Rs7
From
100
200
100
100
200
Figure C.8
Total Cost = Rs5(100) + Rs8(100) + Rs4(200) + Rs9(100) + Rs5(200)
= Rs4,000
26. Special Issues in Modeling
Demand not equal to supply
Called an unbalanced problem
Common situation in the real world
Resolved by introducing dummy
sources or dummy destinations as
necessary with cost coefficients of zero
27. Special Issues in Modeling
Figure C.9
New
Des Moines
capacity
To (A)
Albuquerque
(B)
Boston
(C)
Cleveland
(D) Des Moines
(E) Evansville
(F) Fort Lauderdale
Warehouse
requirement 300 200 200
Factory
capacity
300
300
250
850
Rs5
Rs5
Rs4
Rs4
Rs3
Rs3
Rs9
Rs8
Rs7
From
50200
250
50
150
Dummy
150
0
0
0
150
Total Cost = 250(Rs5) + 50(Rs8) + 200(Rs4) + 50(Rs3) + 150(Rs5) + 150(0)
= Rs3,350
28. Special Issues in Modeling
Degeneracy
To use the stepping-stone methodology,
the number of occupied squares in any
solution must be equal to the number of
rows in the table plus the number of
columns minus 1
If a solution does not satisfy this rule it is
called degenerate
29. To Customer
1
Customer
2
Customer
3
Warehouse 1
Warehouse 2
Warehouse 3
Customer
demand 100 100 100
Warehouse
supply
120
80
100
300
Rs8
Rs7
Rs2
Rs9
Rs6
Rs9
Rs7
Rs10
Rs10
From
Special Issues in Modeling
0 100
100
80
20
Figure C.10
Initial solution is degenerate
Place a zero quantity in an unused square and
proceed computing improvement indices