SlideShare una empresa de Scribd logo
1 de 4
TRANSPORTATION PROBLEM
       Transportation problem is one of the subclasses of LPP’s in which the objective is to
transport various quantities of a single homogeneous commodity, that are initially stored at
various origins to different destinations in such a way that the total transportation cost is
minimum. To achieve this objective we must know the amount and location of available
supplies and the quantities demanded. In addition, we must know the costs that result from
transporting one unit of commodity from various origins to various destinations.

Mathematical Formulation of the Transportation Problem
A transportation problem can be stated mathematically as a Linear Programming Problem as
below:
Minimize Z =
subject to the constraints

         = ai , i = 1, 2,…..,m
         = bj , j = 1, 2,…..,m

    xij ≥ 0 for all i and j
Where, ai = quantity of commodity available at origin i
      bj= quantity of commodity demanded at destination j
      cij= cost of transporting one unit of commodity from ith origin to jth
           destination
      xij = quantity transported from ith origin to jth destination


Tabular form of the Transportation Problem

    To      D1             D2          …….          Dn           Supply
From
    O1       c11           c12        …….           c1n              a1

    O2       c21           c22        …….           c2n              a2

.           .              .          …….           .            .
.           .              .                        .            .
.           .              .                        .            .
    Om       cm1           cm2        …….           cmn               am

Demand          b1         b2         …….               bn
NORTH - WEST CORNER RULE
Step1:Identify the cell at North-West corner of the transportation        matrix.
Step2:Allocate as many units as possible to that cell without      exceeding      supply or
demand; then cross out the row       or column that is exhausted by this assignment
Step3:Reduce the amount of corresponding supply or          demand which is more by allocated
amount.
Step4:Again identify the North-West corner cell of reduced         transportation matrix.
Step5:Repeat Step2 and Step3 until all the rim       requirements are satisfied.

Vogel’s Approximation Method (VAM)

Step-I: Compute the penalty values for each row and each column. The penalty will be
        equal to the difference between the two smallest shipping costs in the row or column.
Step-II: Identify the row or column with the largest penalty. Find the first basic variable which
        has the smallest shipping cost in that row or        column. Then assign the highest
possible        value to that variable, and cross-out the row       or column which is
exhausted.
Step-III: Compute new penalties and repeat the        same procedure until all the rim
        requirements are satisfied.


An example for Vogel’s Method
Find the IBFS of the following transportation problem by using Penalty Method.

                                      D1                 D2                 D3
                                                                                      Supply


                                                                                         10
                                 6                  7                  8


                                                                                         15
                                 15                 80                 78

                                      15                 5                   5


Step 1: Compute the penalties in each row and                               each column .
                                                                                   Supply     Row Penalty


                                                                                    10              7-6=1
                            6                  7                  8


                                                                            Supply 15     78-15=63
                                                                                    Row Penalty
                            15                 80                 78

      Demand                     15                 5                  5      10            7-6=1
Step 2: Identify the largest penalty and choose least cost cell to corresponding this penalty
                   6            7           8
      Column Penalty        15-6=9             80-7=73            78-8=70
                                                                              15         78-15=63
                  15                  80                 78

Demand                 15                  5                  5

Column Penalty     15-6=9              80-7=73            78-8=70
Step-3: Allocate the amount 5 which is minimum of corresponding row supply and column
demand and then cross out column2
                                                                                       Supply        Row Penalty

                                                       5
                                                                                          10            7-6=1
                           6                  7                     8


                                                                                          15          78-15=63
                           15              80                       78

  Demand                        15                 5                     5

  Column Penalty            15-6=9            80-7=73               78-8=70


Step-4: Recalculate the penalties
                                                                             Supply   Row Penalty
                                                   5
                                                                               5         8-6=2
                                6         7                8

                                                                              15       78-15=63
                                15        80               78

          Demand                     15        X                5

          Column Penalty        15-6=9                     78-8=70




                                                                                      Supply        Row Penalty

                                                       5
                                                                                         5             8-6=2
Step-5: Identify the6largest penalty and choose least cost cell to corresponding this penalty
                                7           8


                                                                                        15           78-15=63
                      15                  80                    78

 Demand                        15                 X                      5

 Column Penalty            15-6=9                                   78-8=70
Step-6: Allocate the amount 5 which is minimum of corresponding row supply and column
demand, then cross out column3
                                                                             Supply       Row Penalty

                                                     5                  5
                                                                                 5           8-6=2
                       6                   7                  8


                                                                                 15        78-15=63
                       15                  80                 78

     Demand                 15                  X                  X

     Column Penalty    15-6=9


Step-7: Finally allocate the values 0 and 15 to corresponding cells and cross out column 1

                                 D1                  D2                 D3        Supply

                                      0                   5                  5
                                                                                      X
                  O1        6                   7                  8

                                      15
                                                                                      X
                  O2        15                  80                 78

        Demand                   X                   X                  X



Solution of the problem
Now the Initial Basic Feasible Solution of the transportation problem is
X11=0, X12=5, X13=5, and X21=15 and
Total transportation cost = (0x6)+(5x7)+(5x8)+(15x15)
                        = 0+35+40+225
                        = 300.

Más contenido relacionado

La actualidad más candente

Theory of constraints
Theory of constraintsTheory of constraints
Theory of constraints
MOHD ARISH
 

La actualidad más candente (20)

Unit.5. transportation and assignment problems
Unit.5. transportation and assignment problemsUnit.5. transportation and assignment problems
Unit.5. transportation and assignment problems
 
Replacement Theory Models in Operations Research by Dr. Rajesh Timane
Replacement Theory Models in Operations Research by Dr. Rajesh TimaneReplacement Theory Models in Operations Research by Dr. Rajesh Timane
Replacement Theory Models in Operations Research by Dr. Rajesh Timane
 
Operations research : Assignment problem (One's method) presentation
Operations research : Assignment problem (One's method) presentationOperations research : Assignment problem (One's method) presentation
Operations research : Assignment problem (One's method) presentation
 
Big-M Method Presentation
Big-M Method PresentationBig-M Method Presentation
Big-M Method Presentation
 
Assignment model
Assignment modelAssignment model
Assignment model
 
Transportation model and assignment model
Transportation model and assignment modelTransportation model and assignment model
Transportation model and assignment model
 
Simplex method: Slack, Surplus & Artificial variable
Simplex method:  Slack, Surplus & Artificial variableSimplex method:  Slack, Surplus & Artificial variable
Simplex method: Slack, Surplus & Artificial variable
 
Transportation Problem In Linear Programming
Transportation Problem In Linear ProgrammingTransportation Problem In Linear Programming
Transportation Problem In Linear Programming
 
Sequencing
SequencingSequencing
Sequencing
 
Introduction to Operations Research
Introduction to Operations ResearchIntroduction to Operations Research
Introduction to Operations Research
 
3. linear programming senstivity analysis
3. linear programming senstivity analysis3. linear programming senstivity analysis
3. linear programming senstivity analysis
 
Network Problem CPM & PERT
Network Problem CPM &  PERTNetwork Problem CPM &  PERT
Network Problem CPM & PERT
 
Philosophy of supply chain
Philosophy of supply chainPhilosophy of supply chain
Philosophy of supply chain
 
Transportation problem ppt
Transportation problem pptTransportation problem ppt
Transportation problem ppt
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
 
Logistics-competitive advantage
Logistics-competitive advantageLogistics-competitive advantage
Logistics-competitive advantage
 
Theory of constraints
Theory of constraintsTheory of constraints
Theory of constraints
 
Transportation model
Transportation modelTransportation model
Transportation model
 
Routing and scheduling
Routing and schedulingRouting and scheduling
Routing and scheduling
 
AGGREGATE PRODUCTION PLANNING
AGGREGATE PRODUCTION PLANNING AGGREGATE PRODUCTION PLANNING
AGGREGATE PRODUCTION PLANNING
 

Destacado (13)

Transportation model
Transportation modelTransportation model
Transportation model
 
Uses of Project Status field
Uses of  Project Status field Uses of  Project Status field
Uses of Project Status field
 
layout planning
layout planninglayout planning
layout planning
 
Om problems facility layout
Om problems   facility layoutOm problems   facility layout
Om problems facility layout
 
Ch09
Ch09Ch09
Ch09
 
Location models
Location modelsLocation models
Location models
 
Cable Layout, Continuous Beam & Load Balancing Method
 Cable Layout, Continuous Beam & Load Balancing Method Cable Layout, Continuous Beam & Load Balancing Method
Cable Layout, Continuous Beam & Load Balancing Method
 
Assembly systems & line balance
Assembly systems & line balanceAssembly systems & line balance
Assembly systems & line balance
 
Assembly Line Balancing -Example
Assembly Line Balancing -ExampleAssembly Line Balancing -Example
Assembly Line Balancing -Example
 
Transportation Problem in Operational Research
Transportation Problem in Operational ResearchTransportation Problem in Operational Research
Transportation Problem in Operational Research
 
Line balancing ppt By Wakil Kumar
Line balancing ppt By Wakil KumarLine balancing ppt By Wakil Kumar
Line balancing ppt By Wakil Kumar
 
assembly line balancing
assembly line balancingassembly line balancing
assembly line balancing
 
Assembly Line Balancing
Assembly Line BalancingAssembly Line Balancing
Assembly Line Balancing
 

Más de itsvineeth209

Evolution,Drivers Of Indian Retail
Evolution,Drivers Of Indian RetailEvolution,Drivers Of Indian Retail
Evolution,Drivers Of Indian Retail
itsvineeth209
 
Intro To Tretailing 6.2.09
Intro To Tretailing 6.2.09Intro To Tretailing 6.2.09
Intro To Tretailing 6.2.09
itsvineeth209
 
Indian Retail Sector
Indian Retail SectorIndian Retail Sector
Indian Retail Sector
itsvineeth209
 
Rm 10 Report Writing 2
Rm   10   Report Writing 2Rm   10   Report Writing 2
Rm 10 Report Writing 2
itsvineeth209
 
Rm 6 Sampling Design
Rm   6   Sampling DesignRm   6   Sampling Design
Rm 6 Sampling Design
itsvineeth209
 
Rm 1 Intro Types Research Process
Rm   1   Intro Types   Research ProcessRm   1   Intro Types   Research Process
Rm 1 Intro Types Research Process
itsvineeth209
 
Rm 5 Methods Of Data Collection
Rm   5   Methods Of Data CollectionRm   5   Methods Of Data Collection
Rm 5 Methods Of Data Collection
itsvineeth209
 
Rm 4 Research Design
Rm   4   Research DesignRm   4   Research Design
Rm 4 Research Design
itsvineeth209
 
Rm 2 Problem Identification
Rm   2   Problem IdentificationRm   2   Problem Identification
Rm 2 Problem Identification
itsvineeth209
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
itsvineeth209
 
North West Corner Rule
North   West Corner RuleNorth   West Corner Rule
North West Corner Rule
itsvineeth209
 
Artificial Variable Technique –
Artificial Variable Technique –Artificial Variable Technique –
Artificial Variable Technique –
itsvineeth209
 

Más de itsvineeth209 (20)

Green Marketing
Green MarketingGreen Marketing
Green Marketing
 
Evolution,Drivers Of Indian Retail
Evolution,Drivers Of Indian RetailEvolution,Drivers Of Indian Retail
Evolution,Drivers Of Indian Retail
 
Intro To Tretailing 6.2.09
Intro To Tretailing 6.2.09Intro To Tretailing 6.2.09
Intro To Tretailing 6.2.09
 
Indian Retail Sector
Indian Retail SectorIndian Retail Sector
Indian Retail Sector
 
Sampling Design
Sampling DesignSampling Design
Sampling Design
 
Sampling Design
Sampling DesignSampling Design
Sampling Design
 
Rm 10 Report Writing 2
Rm   10   Report Writing 2Rm   10   Report Writing 2
Rm 10 Report Writing 2
 
Rm 6 Sampling Design
Rm   6   Sampling DesignRm   6   Sampling Design
Rm 6 Sampling Design
 
Rm 1 Intro Types Research Process
Rm   1   Intro Types   Research ProcessRm   1   Intro Types   Research Process
Rm 1 Intro Types Research Process
 
Rm 5 Methods Of Data Collection
Rm   5   Methods Of Data CollectionRm   5   Methods Of Data Collection
Rm 5 Methods Of Data Collection
 
Rm 3 Hypothesis
Rm   3   HypothesisRm   3   Hypothesis
Rm 3 Hypothesis
 
Research Design
Research DesignResearch Design
Research Design
 
Rm 4 Research Design
Rm   4   Research DesignRm   4   Research Design
Rm 4 Research Design
 
Rm 2 Problem Identification
Rm   2   Problem IdentificationRm   2   Problem Identification
Rm 2 Problem Identification
 
Vam
VamVam
Vam
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
 
Simplex Method
Simplex MethodSimplex Method
Simplex Method
 
North West Corner Rule
North   West Corner RuleNorth   West Corner Rule
North West Corner Rule
 
Artificial Variable Technique –
Artificial Variable Technique –Artificial Variable Technique –
Artificial Variable Technique –
 
Combined
CombinedCombined
Combined
 

Último

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
 

Último (20)

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
HTML Injection Attacks: Impact and Mitigation Strategies
HTML Injection Attacks: Impact and Mitigation StrategiesHTML Injection Attacks: Impact and Mitigation Strategies
HTML Injection Attacks: Impact and Mitigation Strategies
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 

Transportation Problem

  • 1. TRANSPORTATION PROBLEM Transportation problem is one of the subclasses of LPP’s in which the objective is to transport various quantities of a single homogeneous commodity, that are initially stored at various origins to different destinations in such a way that the total transportation cost is minimum. To achieve this objective we must know the amount and location of available supplies and the quantities demanded. In addition, we must know the costs that result from transporting one unit of commodity from various origins to various destinations. Mathematical Formulation of the Transportation Problem A transportation problem can be stated mathematically as a Linear Programming Problem as below: Minimize Z = subject to the constraints = ai , i = 1, 2,…..,m = bj , j = 1, 2,…..,m xij ≥ 0 for all i and j Where, ai = quantity of commodity available at origin i bj= quantity of commodity demanded at destination j cij= cost of transporting one unit of commodity from ith origin to jth destination xij = quantity transported from ith origin to jth destination Tabular form of the Transportation Problem To D1 D2 ……. Dn Supply From O1 c11 c12 ……. c1n a1 O2 c21 c22 ……. c2n a2 . . . ……. . . . . . . . . . . . . Om cm1 cm2 ……. cmn am Demand b1 b2 ……. bn NORTH - WEST CORNER RULE
  • 2. Step1:Identify the cell at North-West corner of the transportation matrix. Step2:Allocate as many units as possible to that cell without exceeding supply or demand; then cross out the row or column that is exhausted by this assignment Step3:Reduce the amount of corresponding supply or demand which is more by allocated amount. Step4:Again identify the North-West corner cell of reduced transportation matrix. Step5:Repeat Step2 and Step3 until all the rim requirements are satisfied. Vogel’s Approximation Method (VAM) Step-I: Compute the penalty values for each row and each column. The penalty will be equal to the difference between the two smallest shipping costs in the row or column. Step-II: Identify the row or column with the largest penalty. Find the first basic variable which has the smallest shipping cost in that row or column. Then assign the highest possible value to that variable, and cross-out the row or column which is exhausted. Step-III: Compute new penalties and repeat the same procedure until all the rim requirements are satisfied. An example for Vogel’s Method Find the IBFS of the following transportation problem by using Penalty Method. D1 D2 D3 Supply 10 6 7 8 15 15 80 78 15 5 5 Step 1: Compute the penalties in each row and each column . Supply Row Penalty 10 7-6=1 6 7 8 Supply 15 78-15=63 Row Penalty 15 80 78 Demand 15 5 5 10 7-6=1 Step 2: Identify the largest penalty and choose least cost cell to corresponding this penalty 6 7 8 Column Penalty 15-6=9 80-7=73 78-8=70 15 78-15=63 15 80 78 Demand 15 5 5 Column Penalty 15-6=9 80-7=73 78-8=70
  • 3. Step-3: Allocate the amount 5 which is minimum of corresponding row supply and column demand and then cross out column2 Supply Row Penalty 5 10 7-6=1 6 7 8 15 78-15=63 15 80 78 Demand 15 5 5 Column Penalty 15-6=9 80-7=73 78-8=70 Step-4: Recalculate the penalties Supply Row Penalty 5 5 8-6=2 6 7 8 15 78-15=63 15 80 78 Demand 15 X 5 Column Penalty 15-6=9 78-8=70 Supply Row Penalty 5 5 8-6=2 Step-5: Identify the6largest penalty and choose least cost cell to corresponding this penalty 7 8 15 78-15=63 15 80 78 Demand 15 X 5 Column Penalty 15-6=9 78-8=70
  • 4. Step-6: Allocate the amount 5 which is minimum of corresponding row supply and column demand, then cross out column3 Supply Row Penalty 5 5 5 8-6=2 6 7 8 15 78-15=63 15 80 78 Demand 15 X X Column Penalty 15-6=9 Step-7: Finally allocate the values 0 and 15 to corresponding cells and cross out column 1 D1 D2 D3 Supply 0 5 5 X O1 6 7 8 15 X O2 15 80 78 Demand X X X Solution of the problem Now the Initial Basic Feasible Solution of the transportation problem is X11=0, X12=5, X13=5, and X21=15 and Total transportation cost = (0x6)+(5x7)+(5x8)+(15x15) = 0+35+40+225 = 300.