The Transportation and Assignment Problems. Chapter 9: Hillier and Lieberman Chapter 7: Decision Tools for Agribusiness Dr. Hurley s AGB 328 Course

Size: px
Start display at page:

Download "The Transportation and Assignment Problems. Chapter 9: Hillier and Lieberman Chapter 7: Decision Tools for Agribusiness Dr. Hurley s AGB 328 Course"

Transcription

1 The Transportation and Assignment Problems Chapter 9: Hillier and Lieberman Chapter 7: Decision Tools for Agribusiness Dr. Hurley s AGB 328 Course

2 Terms to Know Sources Destinations Supply Demand The Requirements Assumption The Feasible Solutions Property The Cost Assumption Dummy Destination Dummy Source Transportation Simple Method Northwest Corner Rule Vogel s Approimation Method Russell s Approimation Method Recipient Cells Donor Cells Assignment Problems Assignees Tasks Hungarian Algorithm

3 Case Study: P&T Company P&T is a small family-owned business that processes and cans vegetables and then distributes them for eventual sale One of its main products that it processes and ships is peas These peas are processed in: Bellingham WA; Eugene OR; and Albert Lea MN The peas are shipped to: Sacramento CA; Salt Lake City UT; Rapid City SD; and Albuquerque NM

4 Case Study: P&T Company Shipping Data Cannery Output Warehouse Allocation Bellingham 75 Truckloads Sacramento 80 Truckloads Eugene 125 Truckloads Salt Lake 65 Truckloads Albert Lea 100 Truckloads Rapid City 70 Truckloads Total 300 Truckloads Albuquerque 85 Truckloads Total 300 Truckloads

5 Case Study: P&T Company Shipping Cost/Truckload Warehouse Cannery Sacramento Salt Lake Rapid City Albuquerque Bellingham $464 $513 $654 $ Supply Eugene $352 $416 $690 $ Albert Lea $995 $682 $388 $ Demand

6 Network Presentation of P&T Co. Problem C1 513 W C W2-65 W C1 388 W

7 Mathematical Model for P&T Transportation Problem Minimize

8 Mathematical Model for P&T Transportation Problem Cont. Subject to: = = = = = = = 85 ij 0 (i = 123; j = 1234)

9 Transportation Problems Transportation problems are characterized by problems that are trying to distribute commodities from any supply center known as sources to any group of receiving centers known as destinations Two major assumptions are needed in these types of problems: The Requirements Assumption The Cost Assumption

10 Transportation Assumptions The Requirement Assumption Each source has a fied supply which must be distributed to destinations while each destination has a fied demand that must be received from the sources The Cost Assumption The cost of distributing commodities from the source to the destination is directly proportional to the number of units distributed

11 Feasible Solution Property A transportation problem will have a feasible solution if and only if the sum of the supplies is equal to the sum of the demands. Hence the constraints in the transportation problem must be fied requirement constraints met with equality.

12 The General Model of a Transportation Problem Any problem that attempts to minimize the total cost of distributing units of commodities while meeting the requirement assumption and the cost assumption and has information pertaining to sources destinations supplies demands and unit costs can be formulated into a transportation model

13 Visualizing the Transportation Model When trying to model a transportation model it is usually useful to draw a network diagram of the problem you are eamining A network diagram shows all the sources destinations and unit cost for each source to each destination in a simple visual format like the eample on the net slide

14 Network Diagram Supply Demand S1 Source 1 c 11 c12 Destination 1 -D1 c 1n c 21 c 13 S2 Source 2 c 23 c 22 Destination 2 -D2 S3 Source 3... c 2n c31 c 32 c 33 c 3n c m1cm2 Destination D3 Sm Source m c m3 Destination n -Dn c mn

15 General Mathematical Model of Transportation Problems m n Minimize Z= i=1 j=1 c ij ij Subject to: n ij = s i for I =12 m m i=1 j=1 ij = d j for j = 12 n ij 0 for all i and j

16 Integer Solutions Property If all the supplies and demands have integer values then the transportation problem with feasible solutions is guaranteed to have an optimal solution with integer values for all its decision variables This implies that there is no need to add restrictions on the model to force integer solutions

17 Solving a Transportation Problem When Ecel solves a transportation problem it uses the regular simple method Due to the characteristics of the transportation problem a faster solution can be found using the transportation simple method Unfortunately the transportation simple model is not programmed in Solver

18 Modeling Variants of Transportation Problems In many transportation models you are not going to always see supply equals demand With small problems this is not an issue because the simple method can solve the problem relatively efficiently With large transportation problems it may be helpful to transform the model to fit the transportation simple model

19 Issues That Arise with Transportation Models Some of the issues that may arise are: The sum of supply eceeds the sums of demand The sum of the supplies is less than the sum of demands A destination has both a minimum demand and maimum demand Certain sources may not be able to distribute commodities to certain destinations The objective is to maimize profits rather than minimize costs

20 Method for Handling Supply Not Equal to Demand When supply does not equal demand you can use the idea of a slack variable to handle the ecess A slack variable is a variable that can be incorporated into the model to allow inequality constraints to become equality constraints If supply is greater than demand then you need a slack variable known as a dummy destination If demand is greater than supply then you need a slack variable known as a dummy source

21 Handling Destinations that Cannot Be Delivered To There are two ways to handle the issue when a source cannot supply a particular destination The first way is to put a constraint that does not allow the value to be anything but zero The second way of handling this issue is to put an etremely large number into the cost of shipping that will force the value to equal zero

22 Tetbook Transportation Models Eamined P&T A typical transportation problem Could there be another formulation? Northern Airplane An eample when you need to use the Big M Method and utilizing dummy destinations for ecess supply to fit into the transportation model Metro Water District An eample when you need to use the Big M Method and utilizing dummy sources for ecess demand to fit into the transportation model

23 The Transportation Simple Method While the normal simple method can solve transportation type problems it does not necessarily do it in the most efficient fashion especially for large problems. The transportation simple is meant to solve the problems much more quickly.

24 Finding an Initial Solution for the Transportation Simple Northwest Corner Rule Let sd stand for the amount allocated to supply row s and demand row d For 11 select the minimum of the supply and demand for supply 1 and demand 1 If any supply is remaining then increment over to sd+1 otherwise increment down to s+1d For this net variable select the minimum of the leftover supply or leftover demand for the new row and column you are in Continue until all supply and demand has been allocated

25 Finding an Initial Solution for the Transportation Simple Vogel s Approimation Method For each row and column that has not been deleted calculate the difference between the smallest and second smallest in absolute value terms (ties mean that the difference is zero) In the row or column that has the highest difference find the lowest cost variable in it Set this variable to the minimum of the leftover supply or demand Delete the supply or demand row/column that was the minimum and go back to the top step

26 Finding an Initial Solution for the Transportation Simple Russell s Approimation Method For each remaining source row i determine the largest unit cost c ij and call it u i For each remaining destination column j determine the largest unit cost c ij and call it v i Calculate ij = c ij u i v j for all ij that have not previously been selected Select the largest corresponding ij that has the largest negative ij Allocate to this variable as much as feasible based on the current supply and demand that are leftover

27 Algorithm for Transportation Simple Method Construct initial basic feasible solution Optimality Test Derive a set of u i and v j by setting the u i corresponding to the row that has the most amount of allocations to zero and solving the leftover set of equations for c ij = u i + v j If all c ij u i v j 0 for every (ij) such that ij is nonbasic then stop. Otherwise do an iteration.

28 Algorithm for Transportation Simple Method Cont. An Iteration Determine the entering basic variable by selecting the nonbasic variable having the largest negative value for c ij u i v j Determine the leaving basic variable by identifying the chain of swaps required to maintain feasibility Select the basic variable having the smallest variable from the donor cells Determine the new basic feasible solution by adding the value of the leaving basic variable to the allocation for each recipient cell. Subtract this value from the allocation of each donor cell

29 Assignment Problems Assignment problems are problems that require tasks to be handed out to assignees in the cheapest method possible The assignment problem is a special case of the transportation problem

30 Characteristics of Assignment Problems The number of assignees and the number of task are the same Each assignee is to be assigned eactly one task Each task is to be assigned by eactly one assignee There is a cost associated with each combination of an assignee performing a task The objective is to determine how all of the assignments should be made to minimize the total cost

31 General Mathematical Model of Assignment Problems n n Minimize Z= i=1 j=1 c ij ij Subject to: n ij = 1 for I =12 m n i=1 j=1 ij = 1 for j = 12 n ij is binary for all i and j

32 Modeling Variants of the Assignment Problem Issues that arise: Certain assignees are unable to perform certain tasks. There are more task than there are assignees implying some tasks will not be completed. There are more assignees than there are tasks implying some assignees will not be given a task. Each assignee can be given multiple tasks simultaneously. Each task can be performed jointly by more than one assignee.

33 Assignment Spreadsheet Models from Tetbook Job Shop Company Better Products Company We will eamine these spreadsheets in class and derive mathematical models from the spreadsheets

34 Hungarian Algorithm for Solving Assignment Problems Step 1: Find the minimum from each row and subtract from every number in the corresponding row making a new table Step 2: Find the minimum from each column and subtract from every number in the corresponding column making a new table Step 3: Test to see whether an optimal assignment can be made by eamining the minimum number of lines needed to cover all the zeros If the number of lines corresponds to the number of rows you have the optimal and you should go to step 6 If the number of lines does not correspond to the number of rows go to step 4

35 Hungarian Algorithm for Solving Assignment Problems Cont. Step 4: Modify the table by using the following: Subtract the smallest uncovered number from every uncovered number in the table Add the smallest uncovered number to the numbers of intersected lines All other numbers stay unchanged Step 5: Repeat steps 3 and four until you have the optimal set

36 Hungarian Algorithm for Solving Assignment Problems Cont. Step 6: Make the assignment to the optimal set one at a time focusing on the zero elements Start with the rows and columns that have only one zero Once an optimal assignment has been given to a variable cross that row and column out Continue until all the rows and columns with only one zero have been allocated Net do the columns/rows with two non crossed out zeroes as above Continue until all assignments have been made

37 In Class Activity (Not Graded) Attempt to find an initial solution to the P&T problem using the a) Northwest Corner Rule b) Vogel s Approimation Method and c) Russell s Approimation Method 9.1-3b set up the problem as a regular linear programming problem and solve using solver then set the problem up as a transportation problem and solve using solver

38 In Class Activity (Not Graded) Solve the following problem using the Hungarian method.

39 Case Study: Sellmore Company Cont. The assignees for the task are: Ann Ian Joan Sean A summary of each assignees productivity and costs are given on the net slide.

40 Case Study: Sellmore Company Cont. Employee Word Processing Required Time Per Task Graphics Packets Registration Wage Ann $14 Ian $12 Joan $13 Sean $15

41 Assignment of Variables ij i = 1 for Ann 2 for Ian 3 for Joan 4 for Sean j = 1 for Processing 2 for Graphics 3 for Packets 4 for Registration

42 Mathematical Model for Sellmore Company Minimize

43 Mathematical Model for Sellmore Company Cont : to Subject

The Transportation and Assignment Problems. Hillier &Lieberman Chapter 8

The Transportation and Assignment Problems. Hillier &Lieberman Chapter 8 The Transportation and Assignment Problems Hillier &Lieberman Chapter 8 The Transportation and Assignment Problems Two important special types of linear programming problems The transportation problem

More information

ISE 204 OR II. Chapter 8 The Transportation and Assignment Problems. Asst. Prof. Dr. Deniz TÜRSEL ELİİYİ

ISE 204 OR II. Chapter 8 The Transportation and Assignment Problems. Asst. Prof. Dr. Deniz TÜRSEL ELİİYİ ISE 204 OR II Chapter 8 The Transportation and Assignment Problems Asst. Prof. Dr. Deniz TÜRSEL ELİİYİ 1 The Transportation and Assignment Problems Transportation Problems: A special class of Linear Programming

More information

TRANSPORTATION PROBLEM AND VARIANTS

TRANSPORTATION PROBLEM AND VARIANTS TRANSPORTATION PROBLEM AND VARIANTS Introduction to Lecture T: Welcome to the next exercise. I hope you enjoyed the previous exercise. S: Sure I did. It is good to learn new concepts. I am beginning to

More information

CHAPTER 4 A NEW ALTERNATE METHOD OF TRANS-SHIPMENT PROBLEM

CHAPTER 4 A NEW ALTERNATE METHOD OF TRANS-SHIPMENT PROBLEM 56 CHAPTER 4 A NEW ALTERNATE METHOD OF TRANS-SHIPMENT PROBLEM 4.1 Introduction In a transportation problem shipment of commodity takes place among sources and destinations. But instead of direct shipments

More information

Transshipment. Chapter 493. Introduction. Data Structure. Example Model

Transshipment. Chapter 493. Introduction. Data Structure. Example Model Chapter 493 Introduction The transshipment model is a special case of the minimum cost capacitated flow model in which there are no capacities or minimums on the arc flows. The transshipment model is similar

More information

Transportation Problem

Transportation Problem Transportation Problem MIGUEL A. S. CASQUILHO Technical University of Lisbon, Ave. Rovisco Pais, 1049-001 Lisboa, Portugal The Transportation Problem is briefly presented, together with other problems

More information

Transportation problem

Transportation problem Transportation problem Operations research (OR) are concerned with scientifically deciding how to best design and operate people machine systems, usually under conditions requiring the allocation of scarce

More information

A Production Problem

A Production Problem Session #2 Page 1 A Production Problem Weekly supply of raw materials: Large Bricks Small Bricks Products: Table Profit = $20/Table Chair Profit = $15/Chair Session #2 Page 2 Linear Programming Linear

More information

Transshipment and Assignment Models

Transshipment and Assignment Models March 31, 2009 Goals of this class meeting 2/ 5 Learn how to formulate transportation models with intermediate points. Learn how to use the transportation model framework for finding optimal assignments.

More information

3. Transportation Problem (Part 1)

3. Transportation Problem (Part 1) 3 Transportation Problem (Part 1) 31 Introduction to Transportation Problem 32 Mathematical Formulation and Tabular Representation 33 Some Basic Definitions 34 Transportation Algorithm 35 Methods for Initial

More information

Transportation Problems

Transportation Problems C H A P T E R 11 Transportation Problems Learning Objectives: Understanding the feature of Assignment Problems. Formulate an Assignment problem. Hungarian Method Unbalanced Assignment Problems Profit Maximization

More information

University Question Paper Two Marks

University Question Paper Two Marks University Question Paper Two Marks 1. List the application of Operations Research in functional areas of management. Answer: Finance, Budgeting and Investment Marketing Physical distribution Purchasing,

More information

Operation and supply chain management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology Madras

Operation and supply chain management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology Madras Operation and supply chain management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology Madras Lecture - 37 Transportation and Distribution Models In this lecture, we

More information

The Study of Using LP to Solve Flower Transport Problem

The Study of Using LP to Solve Flower Transport Problem The Study of Using LP to Solve Flower Transport Problem 1 Chung-Hsin Liu, 2 Le Le Trung 1 Department of Computer Science & Information Engineering, Chinese Culture University, Taiwan, R.O.C. liu3.gold@msa.hinet.net

More information

Keywords: Transportation problem; initial solution; distribution; algorithm; VAM, LC, NWC

Keywords: Transportation problem; initial solution; distribution; algorithm; VAM, LC, NWC American International Journal of Research in Science, Technology, Engineering & Mathematics Available online at http://www.iasir.net ISSN (Print): 2328-3491, ISSN (Online): 2328-3580, ISSN (CD-ROM): 2328-3629

More information

Basic Linear Programming Concepts. Lecture 2 (3/29/2017)

Basic Linear Programming Concepts. Lecture 2 (3/29/2017) Basic Linear Programming Concepts Lecture 2 (3/29/2017) Definition Linear Programming (LP) is a mathematical method to allocate scarce resources to competing activities in an optimal manner when the problem

More information

DEA Model: A Key Technology for the Future

DEA Model: A Key Technology for the Future International Journal of Engineering Science Invention ISSN (Online): 2319 6734, ISSN (Print): 2319 6726 Volume 5 Issue 12 December 2016 PP. 30-33 DEA Model: A Key Technology for the Future Seema Shokeen

More information

International Journal of Mathematics Trends and Technology (IJMTT) Volume 44 Number 4 April 2017

International Journal of Mathematics Trends and Technology (IJMTT) Volume 44 Number 4 April 2017 Solving Transportation Problem by Various Methods and Their Comaprison Dr. Shraddha Mishra Professor and Head Lakhmi Naraian College of Technology, Indore, RGPV BHOPAL Abstract: The most important and

More information

DEVELOPMENT OF A DYNAMIC PROGRAMMING MODEL FOR OPTIMIZING PRODUCTION PLANNING. the Polytechnic Ibadan, Mechatronics Engineering Department; 3, 4

DEVELOPMENT OF A DYNAMIC PROGRAMMING MODEL FOR OPTIMIZING PRODUCTION PLANNING. the Polytechnic Ibadan, Mechatronics Engineering Department; 3, 4 DEVELOPMENT OF A DYNAMIC PROGRAMMING MODEL FOR OPTIMIZING PRODUCTION PLANNING 1 Olanrele, O.O., 2 Olaiya, K. A., 3 Aderonmu, M.A., 4 Adegbayo, O.O., 5 Sanusi, B.Y. 1, 2,5 the Polytechnic Ibadan, Mechatronics

More information

TRANSPORTATION MODEL IN DELIVERY GOODS USING RAILWAY SYSTEMS

TRANSPORTATION MODEL IN DELIVERY GOODS USING RAILWAY SYSTEMS TRANSPORTATION MODEL IN DELIVERY GOODS USING RAILWAY SYSTEMS Fauziah Ab Rahman Malaysian Institute of Marine Engineering Technology Universiti Kuala Lumpur Lumut, Perak, Malaysia fauziahabra@unikl.edu.my

More information

A comparative study of ASM and NWCR method in transportation problem

A comparative study of ASM and NWCR method in transportation problem Malaya J. Mat. 5(2)(2017) 321 327 A comparative study of ASM and NWCR method in transportation problem B. Satheesh Kumar a, *, R. Nandhini b and T. Nanthini c a,b,c Department of Mathematics, Dr. N. G.

More information

Balancing a transportation problem: Is it really that simple?

Balancing a transportation problem: Is it really that simple? Original Article Balancing a transportation problem: Is it really that simple? Francis J. Vasko a, * and Nelya Storozhyshina b a Mathematics Department, Kutztown University, Kutztown, Pennsylvania 19530,

More information

Effect of Transportation Model on Organizational Performance: A Case Study of MTN Nigeria, Asaba, Delta State, Nigeria

Effect of Transportation Model on Organizational Performance: A Case Study of MTN Nigeria, Asaba, Delta State, Nigeria International Journal of Innovative Social Sciences & Humanities Research 6(2):76-82, April-June, 2018 SEAHI PUBLICATIONS, 2018 www.seahipaj.org ISSN: 2354-2926 Effect of Transportation Model on Organizational

More information

Optimal Solution of Transportation Problem Based on Revised Distribution Method

Optimal Solution of Transportation Problem Based on Revised Distribution Method Optimal Solution of Transportation Problem Based on Revised Distribution Method Bindu Choudhary Department of Mathematics & Statistics, Christian Eminent College, Indore, India ABSTRACT: Transportation

More information

Locomotive Fuelling Problem (LFP) in Railroad Operations. Bodhibrata Nag 1 & Katta G.Murty 2

Locomotive Fuelling Problem (LFP) in Railroad Operations. Bodhibrata Nag 1 & Katta G.Murty 2 1 Locomotive Fuelling Problem (LFP) in Railroad Operations Bodhibrata Nag 1 & Katta G.Murty 2 About 75% of the world s railroads operate with diesel fuel. Even though European railroads rely on electric

More information

Techniques of Operations Research

Techniques of Operations Research Techniques of Operations Research C HAPTER 2 2.1 INTRODUCTION The term, Operations Research was first coined in 1940 by McClosky and Trefthen in a small town called Bowdsey of the United Kingdom. This

More information

TRANSPORTATION PROBLEM FOR OPTIMALITY

TRANSPORTATION PROBLEM FOR OPTIMALITY Asia Pacific Journal of Research Vol: I. Issue XXXIV, December 01 ISSN: 0-04, E-ISSN-4-49 TRANSPORTATION PROBLEM FOR OPTIMALITY Mrs. M.Vijaya Lakshmi 1 & Mr. V. Hareeswarudu 1& Assistant Professor, Department

More information

An Alternative Method to Find Initial Basic Feasible Solution of a Transportation Problem

An Alternative Method to Find Initial Basic Feasible Solution of a Transportation Problem Annals of Pure and Applied Mathematics Vol., No. 2, 2, 3-9 ISSN: 2279-087X (P), 2279-0888(online) Published on 6 November 2 www.researchmathsci.org Annals of An Alternative Method to Find Initial Basic

More information

Simplex Method Linear Program Application In Process Of Transition To Reduce Use Of Products In Polyster Material In Indonesia

Simplex Method Linear Program Application In Process Of Transition To Reduce Use Of Products In Polyster Material In Indonesia Simplex Method Linear Program Application In Process Of Transition To Reduce Use Of Products In Polyster Material In Indonesia Sukanta, Anwar Ilmar Ramadhan Abstract: PT Asia Pacific Fibers Tbk is a leading

More information

A New Technique for Solving Transportation Problems by Using Decomposition-Based Pricing and its Implementation in Real Life

A New Technique for Solving Transportation Problems by Using Decomposition-Based Pricing and its Implementation in Real Life Dhaka Univ. J. Sci. 64(1): 45-50, 2016 (January) A New Technique for Solving Transportation Problems by Using Decomposition-Based Pricing and its Implementation in Real Life Sajal Chakroborty and M. Babul

More information

Network Flows. 7. Multicommodity Flows Problems. Fall 2010 Instructor: Dr. Masoud Yaghini

Network Flows. 7. Multicommodity Flows Problems. Fall 2010 Instructor: Dr. Masoud Yaghini In the name of God Network Flows 7. Multicommodity Flows Problems 7.1 Introduction Fall 2010 Instructor: Dr. Masoud Yaghini Introduction Introduction In many application contexts, several physical commodities,

More information

Using Binary Integer Programming to Deal with Yesor-No. Chapter 7: Hillier and Hillier

Using Binary Integer Programming to Deal with Yesor-No. Chapter 7: Hillier and Hillier Using Binary Integer Programming to Deal with Yesor-No Decisions Chapter 7: Hillier and Hillier 1 Agenda Case Study: California Manufacturing Company Wyndor Case Revisited Variation of Wyndor s Problem

More information

WAYNE STATE UNIVERSITY Department of Industrial and Manufacturing Engineering May, 2010

WAYNE STATE UNIVERSITY Department of Industrial and Manufacturing Engineering May, 2010 WAYNE STATE UNIVERSITY Department of Industrial and Manufacturing Engineering May, 2010 PhD Preliminary Examination Candidate Name: 1- Sensitivity Analysis (20 points) Answer ALL Questions Question 1-20

More information

Application of Transportation Linear Programming Algorithms to Cost Reduction in Nigeria Soft Drinks Industry

Application of Transportation Linear Programming Algorithms to Cost Reduction in Nigeria Soft Drinks Industry Application of Transportation Linear Programming Algorithms to Cost Reduction in Nigeria Soft Drinks Industry A. O. Salami Abstract The transportation problems are primarily concerned with the optimal

More information

ISSN: Int. J. Adv. Res. 6(1), RESEARCH ARTICLE...

ISSN: Int. J. Adv. Res. 6(1), RESEARCH ARTICLE... Journal Homepage: - www.journalijar.com Article DOI: 10.21474/IJAR01/6381 DOI URL: http://dx.doi.org/10.21474/ijar01/6381 RESEARCH ARTICLE APPROIMATION VOGELS EFFECTIVENESS METHOD (VAM) MINIMIZE COST OF

More information

A Minimum Spanning Tree Approach of Solving a Transportation Problem

A Minimum Spanning Tree Approach of Solving a Transportation Problem International Journal of Mathematics and Statistics Invention (IJMSI) E-ISSN: 2321 4767 P-ISSN: 2321-4759 Volume 5 Issue 3 March. 2017 PP-09-18 A Minimum Spanning Tree Approach of Solving a Transportation

More information

Branch and Bound Method

Branch and Bound Method Branch and Bound Method The Branch and Bound (B&B) is a strategy to eplore the solution space based on the implicit enumeration of the solutions : B&B eamines disjoint subsets of solutions (branching)

More information

2. Solve the following LPP by Graphical method

2. Solve the following LPP by Graphical method DHANALAKSHMI SRINIVASAN ENGINEERING COLLEGE PERAMBALUR DEPARTMENT OF SCIENCE AND HUMANITIES QUESTION BANK BA6122 OPERATIONS RESEARCH UNIT-I LINEAR PROGRAMMING MODELS PART-A 1. What is operations research?

More information

CIS QA LEVEL 2 WEEK 5 TOPIC: LINEAR PROGRAMMING OBJECTIVE AND SHORT ANSWER QUESTIONS

CIS QA LEVEL 2 WEEK 5 TOPIC: LINEAR PROGRAMMING OBJECTIVE AND SHORT ANSWER QUESTIONS CIS QA LEVEL 2 WEEK 5 TOPIC: LINEAR PROGRAMMING OBJECTIVE AND SHORT ANSWER QUESTIONS 1. In the graphical method of solving a Linear Programming problem, the feasible region is the region containing A.

More information

1. are generally independent of the volume of units produced and sold. a. Fixed costs b. Variable costs c. Profits d.

1. are generally independent of the volume of units produced and sold. a. Fixed costs b. Variable costs c. Profits d. Final Exam 61.252 Introduction to Management Sciences Instructor: G. V. Johnson December 17, 2002 1:30 p.m. to 3:30 p.m. Room 210-224 University Centre Seats 307-328 Paper No. 492 Model Building: Break-Even

More information

ISyE 3133B Sample Final Tests

ISyE 3133B Sample Final Tests ISyE 3133B Sample Final Tests Time: 160 minutes, 100 Points Set A Problem 1 (20 pts). Head & Boulders (H&B) produces two different types of shampoos A and B by mixing 3 raw materials (R1, R2, and R3).

More information

Linear Programming: Basic Concepts

Linear Programming: Basic Concepts Linear Programming: Basic Concepts Irwin/McGraw-Hill 1.١ The McGraw-Hill Companies, Inc., 2003 Introduction The management of any organization make Decision about how to allocate its resources to various

More information

LECTURE 41: SCHEDULING

LECTURE 41: SCHEDULING LECTURE 41: SCHEDULING Learning Objectives After completing the introductory discussion on Scheduling, the students would be able to understand what scheduling is and how important it is to high volume

More information

OPERATIONS RESEARCH Code: MB0048. Section-A

OPERATIONS RESEARCH Code: MB0048. Section-A Time: 2 hours OPERATIONS RESEARCH Code: MB0048 Max.Marks:140 Section-A Answer the following 1. Which of the following is an example of a mathematical model? a. Iconic model b. Replacement model c. Analogue

More information

LINEAR PROGRAMMING IEOR 162 Instructor Juan Carlos Muñoz

LINEAR PROGRAMMING IEOR 162 Instructor Juan Carlos Muñoz UNIVERSITY OF CALIFORNIA Industrial Engineering and Operations Research Midterm Eam Spring 0 LINEAR PROGRAMMING IEOR 6 Instructor Juan Carlos Muñoz Attempt all four questions. Show all your work. If you

More information

DIS 300. Quantitative Analysis in Operations Management. Instructions for DIS 300-Transportation

DIS 300. Quantitative Analysis in Operations Management. Instructions for DIS 300-Transportation Instructions for -Transportation 1. Set up the column and row headings for the transportation table: Before we can use Excel Solver to find a solution to C&A s location decision problem, we need to set

More information

CHAPTER 5 SUPPLIER SELECTION BY LEXICOGRAPHIC METHOD USING INTEGER LINEAR PROGRAMMING

CHAPTER 5 SUPPLIER SELECTION BY LEXICOGRAPHIC METHOD USING INTEGER LINEAR PROGRAMMING 93 CHAPTER 5 SUPPLIER SELECTION BY LEXICOGRAPHIC METHOD USING INTEGER LINEAR PROGRAMMING 5.1 INTRODUCTION The SCMS model is solved using Lexicographic method by using LINGO software. Here the objectives

More information

Model Question Paper with Solution

Model Question Paper with Solution Annexure P Model Question Paper with Solution Section A (Very Short Answer Questions) Q.1. Write down three differences between PERT and CPM in brief? Ans.1. The Program Evaluation and Review Technique

More information

Sorting. Bubble Sort. Chapter 9 (Fall 2016, CSUS) Chapter 9.1

Sorting. Bubble Sort. Chapter 9 (Fall 2016, CSUS) Chapter 9.1 Sorting Chapter 9 (Fall 6, CSUS) Bubble Sort Chapter 9. Sorting Often, computers needs to sort a list to put it in specific order Examples: sorting scores by highest to lowest sorting filenames in alphabetical

More information

Operations and Supply Chain Management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras

Operations and Supply Chain Management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Operations and Supply Chain Management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Module - 1 Lecture - 7 Aggregate Planning, Dynamic Programming, Backordering

More information

Modeling Using Linear Programming

Modeling Using Linear Programming Chapter Outline Developing Linear Optimization Models Decision Variables Objective Function Constraints Softwater Optimization Model OM Applications of Linear Optimization OM Spotlight: Land Management

More information

GREY FUZZY MULTIOBJECTIVE OPTIMIZATION MODEL FOR RIVER WATER QUALITY MANAGEMENT

GREY FUZZY MULTIOBJECTIVE OPTIMIZATION MODEL FOR RIVER WATER QUALITY MANAGEMENT GREY FUZZY MULTIOBJECTIVE OPTIMIZATION MODEL FOR RIVER WATER QUALITY MANAGEMENT Subhankar Karmakar and P. P. Mujumdar Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India.

More information

Statistical Investigation of Various Methods to Find the Initial Basic Feasible Solution of a Transportation Problem

Statistical Investigation of Various Methods to Find the Initial Basic Feasible Solution of a Transportation Problem Statistical Investigation of Various Methods to Find the Initial Basic Feasible Solution of a Transportation Problem Ravi Kumar R 1, Radha Gupta 2, Karthiyayini.O 3 1,2,3 PESIT-Bangalore South Campus,

More information

Transportation Theory and Applications

Transportation Theory and Applications Fall 2017 - MTAT.08.043 Transportation Theory and Applications Lecture I: Introduction A. Hadachi Course Syllabus Lecturer: Amnir Hadachi Course website: https://courses.cs.ut.ee/2017/transport/fall Office

More information

Getting Started with OptQuest

Getting Started with OptQuest Getting Started with OptQuest What OptQuest does Futura Apartments model example Portfolio Allocation model example Defining decision variables in Crystal Ball Running OptQuest Specifying decision variable

More information

The Efficient Allocation of Individuals to Positions

The Efficient Allocation of Individuals to Positions The Efficient Allocation of Individuals to Positions by Aanund Hylland and Richard Zeckhauser Presented by Debreu Team: Justina Adamanti, Liz Malm, Yuqing Hu, Krish Ray Hylland and Zeckhauser consider

More information

Optimization Prof. Debjani Chakraborty Department of Mathematics Indian Institute of Technology, Kharagpur

Optimization Prof. Debjani Chakraborty Department of Mathematics Indian Institute of Technology, Kharagpur Optimization Prof. Debjani Chakraborty Department of Mathematics Indian Institute of Technology, Kharagpur Lecture - 39 Multi Objective Decision Making Decision making problem is a process of selection

More information

Review Article Minimizing Costs Can Be Costly

Review Article Minimizing Costs Can Be Costly Advances in Decision Sciences Volume 2010, Article ID 707504, 16 pages doi:10.1155/2010/707504 Review Article Minimizing Costs Can Be Costly Rasmus Rasmussen Institute of Economics, Molde University College

More information

Lecture 5: Minimum Cost Flows. Flows in a network may incur a cost, such as time, fuel and operating fee, on each link or node.

Lecture 5: Minimum Cost Flows. Flows in a network may incur a cost, such as time, fuel and operating fee, on each link or node. Lecture 5: Minimum Cost Flows Flows in a network may incur a cost, such as time, fuel and operating fee, on each link or node. Min Cost Flow Problem Examples Supply chain management deliver goods using

More information

Introduction to Management Science, 10e (Taylor) Chapter 4 Linear Programming: Modeling Examples

Introduction to Management Science, 10e (Taylor) Chapter 4 Linear Programming: Modeling Examples Introduction to Management Science, 10e (Taylor) Chapter 4 Linear Programming: Modeling Examples 1) When formulating a linear programming problem constraint, strict inequality signs (i.e., less than

More information

Modeling Linear Programming Problem Using Microsoft Excel Solver

Modeling Linear Programming Problem Using Microsoft Excel Solver Modeling Linear Programming Problem Using Microsoft Excel Solver ADEKUNLE Simon Ayo* & TAFAMEL Andrew Ehiabhi (Ph.D) Department of Business Administration, Faculty of Management Sciences, University of

More information

Comparison of Statistical Packages in Solving Transportation Problems

Comparison of Statistical Packages in Solving Transportation Problems ISSN No. 976-5697 Volume 4, No. 1, Sep-Oct 213 International Journal of Advanced Research in Computer Science RESEARCH PAPER Available Online at www.ijarcs.info Comparison of Statistical Packages in Solving

More information

Assignment Technique for solving Transportation Problem A Case Study

Assignment Technique for solving Transportation Problem A Case Study Assignment Technique for solving Transportation Problem A Case Study N. Santosh Ranganath Faculty Member, Department of Commerce and Management Studies Dr. B. R. Ambedkar University, Srikakulam, Andhra

More information

ISE480 Sequencing and Scheduling

ISE480 Sequencing and Scheduling ISE480 Sequencing and Scheduling INTRODUCTION ISE480 Sequencing and Scheduling 2012 2013 Spring term What is Scheduling About? Planning (deciding what to do) and scheduling (setting an order and time for

More information

WEIGHTED COST OPPORTUNITY BASED ALGORITHM FOR INITIAL BASIC FEASIBLE SOLUTION: A NEW APPROACH IN TRANSPORTATION PROBLEM

WEIGHTED COST OPPORTUNITY BASED ALGORITHM FOR INITIAL BASIC FEASIBLE SOLUTION: A NEW APPROACH IN TRANSPORTATION PROBLEM Journal of Engineering Science 08(1), 2017, 63-70 JES an international Journal WEIGHTED COST OPPORTUNITY BASED ALGORITHM FOR INITIAL BASIC FEASIBLE SOLUTION: A NEW APPROACH IN TRANSPORTATION PROBLEM A.R.M.

More information

MARTIN de TOURS SCHOOL OF MANAGEMENT DEPARTMENT OF MARKETING LESSON PLAN MKT4829 MARKETING DECISION MAKING

MARTIN de TOURS SCHOOL OF MANAGEMENT DEPARTMENT OF MARKETING LESSON PLAN MKT4829 MARKETING DECISION MAKING MARTIN de TOURS SCHOOL OF MANAGEMENT DEPARTMENT OF MARKETING LESSON PLAN MKT4829 MARKETING DECISION MAKING MKT4829 MARKETING DECISION MAKING MKT4829: Marketing Decision Making COURSE DESCRIPTION This is

More information

INTERIOR POINT ALGORITHM FOR SOLVING FARM RESOURCE ALLOCATION PROBLEM

INTERIOR POINT ALGORITHM FOR SOLVING FARM RESOURCE ALLOCATION PROBLEM Applied Studies in Agribusiness and Commerce APSTRACT Center-Print Publishing House, Debrecen DOI: 10.19041/APSTRACT/2017/1-2/6 SCIENTIFIC PAPER INTERIOR POINT ALGORITHM FOR SOLVING FARM RESOURCE ALLOCATION

More information

Guided Study Program in System Dynamics System Dynamics in Education Project System Dynamics Group MIT Sloan School of Management 1

Guided Study Program in System Dynamics System Dynamics in Education Project System Dynamics Group MIT Sloan School of Management 1 Guided Study Program in System Dynamics System Dynamics in Education Project System Dynamics Group MIT Sloan School of Management 1 Solutions to Assignment #12 January 22, 1999 Reading Assignment: Please

More information

Guided Study Program in System Dynamics System Dynamics in Education Project System Dynamics Group MIT Sloan School of Management 1

Guided Study Program in System Dynamics System Dynamics in Education Project System Dynamics Group MIT Sloan School of Management 1 Guided Study Program in System Dynamics System Dynamics in Education Project System Dynamics Group MIT Sloan School of Management 1 Solutions to Assignment #12 January 22, 1999 Reading Assignment: Please

More information

Managing Low-Volume Road Systems for Intermittent Use

Managing Low-Volume Road Systems for Intermittent Use 224 TRANSPORTATION RESEARCH RECORD 1291 Managing Low-Volume Road Systems for Intermittent Use JERRY ANDERSON AND JOHN SESSIONS In some areas of the United States, particularly in gentle topography, closely

More information

Application of Linear Programming Techniques to Determine the Type and Quantity of Textile Dyed Fabrics

Application of Linear Programming Techniques to Determine the Type and Quantity of Textile Dyed Fabrics Application of Linear Programming Techniques to Determine the Type and Quantity of Textile Dyed Fabrics Gera Workie 1, Abebaw Bizuneh 2, Senait Asmelash 3 Ethiopian Institute of Textile and Fashion Technology

More information

Programmed to pass. calculate the shadow price of direct labour

Programmed to pass. calculate the shadow price of direct labour Programmed to pass Ian Janes, CIMA course leader at Newport Business School, supplies and explains the answers to the supplementary question asked in March 2011 Financial Management s graphical linear

More information

Clock-Driven Scheduling

Clock-Driven Scheduling NOTATIONS AND ASSUMPTIONS: UNIT-2 Clock-Driven Scheduling The clock-driven approach to scheduling is applicable only when the system is by and large deterministic, except for a few aperiodic and sporadic

More information

Discrete and dynamic versus continuous and static loading policy for a multi-compartment vehicle

Discrete and dynamic versus continuous and static loading policy for a multi-compartment vehicle European Journal of Operational Research 174 (2006) 1329 1337 Short Communication Discrete and dynamic versus continuous and static loading policy for a multi-compartment vehicle Yossi Bukchin a, *, Subhash

More information

Using Transportation Model for Aggregate Planning: A Case Study in Soft Drinks Industry

Using Transportation Model for Aggregate Planning: A Case Study in Soft Drinks Industry Journal of Logistics Management 218, 7(1): 11-46 DI: 1.5923/j.logistics.21871.2 Using Transportation Model for Aggregate Planning: A Case Study in Soft Drinks Industry Suhada. Tayyeh *, Saffa J. Abdul-Hussien

More information

Mixed Constraint Fuzzy Transshipment Problem

Mixed Constraint Fuzzy Transshipment Problem Applied Mathematical Sciences, Vol. 6, 2012, no. 48, 2385-2394 Mixed Constraint Fuzzy Transshipment Problem A. Nagoor Gani PG & Research Department of Mathematics Jamal Mohamed College (Autonomous) Tiruchirappalli-620020,

More information

JOB SHOP SCHEDULING TO MINIMIZE WORK-IN-PROCESS, EARLINESS AND TARDINESS COSTS ZHU ZHECHENG A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

JOB SHOP SCHEDULING TO MINIMIZE WORK-IN-PROCESS, EARLINESS AND TARDINESS COSTS ZHU ZHECHENG A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY JOB SHOP SCHEDULING TO MINIMIZE WORK-IN-PROCESS, EARLINESS AND TARDINESS COSTS ZHU ZHECHENG A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING NATIONAL

More information

A Study on North East Corner Method in Transportation Problem of Operations Research and using of Object Oriented Programming Model

A Study on North East Corner Method in Transportation Problem of Operations Research and using of Object Oriented Programming Model Intern. J. Fuzzy Mathematical Archive Vol. 14, No. 1, 2017, 35-40 ISSN: 2320 3242 (P), 2320 3250 (online) Published on 11 December 2017 www.researchmathsci.org DOI: http://dx.doi.org/10.22457/ijfma.v14n1a5

More information

David Besanko and Ronald Braeutigam. Prepared by Katharine Rockett Dieter Balkenborg. Microeconomics, 2 nd Edition

David Besanko and Ronald Braeutigam. Prepared by Katharine Rockett Dieter Balkenborg. Microeconomics, 2 nd Edition Microeconomics, nd Edition David esanko and Ronald raeutigam Chapter : General Equilibrium Theory Prepared by Katharine Rockett Dieter alkenborg 00 John Wiley & Sons, Inc. Trade involves more than one

More information

Excel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray)

Excel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray) Gebauer/Matthews: MIS 213 Hands-on Tutorials and Cases, Spring 2015 111 Excel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray) Purpose: Using Excel Solver as a Decision Support

More information

Applied Data Analysis (Operations Research)

Applied Data Analysis (Operations Research) Applied Data Analysis (Operations Research) Pongsa Pornchaiwiseskul Pongsa.P@chula.ac.th http://j.mp/pongsa Faculty of Economics Chulalongkorn University Pongsa Pornchaiwiseskul, Faculty of Economics,

More information

CHAPTER 1: Introduction to Data Analysis and Decision Making

CHAPTER 1: Introduction to Data Analysis and Decision Making CHAPTER 1: Introduction to Data Analysis and Decision Making MULTIPLE CHOICE 1. The decision-making concepts covered in Data Analysis & Decision Making book include which of the following? a. Optimization

More information

LOADING AND SEQUENCING JOBS WITH A FASTEST MACHINE AMONG OTHERS

LOADING AND SEQUENCING JOBS WITH A FASTEST MACHINE AMONG OTHERS Advances in Production Engineering & Management 4 (2009) 3, 127-138 ISSN 1854-6250 Scientific paper LOADING AND SEQUENCING JOBS WITH A FASTEST MACHINE AMONG OTHERS Ahmad, I. * & Al-aney, K.I.M. ** *Department

More information

A New Fuzzy Modeling Approach for Joint Manufacturing Scheduling and Shipping Decisions

A New Fuzzy Modeling Approach for Joint Manufacturing Scheduling and Shipping Decisions A New Fuzzy Modeling Approach for Joint Manufacturing Scheduling and Shipping Decisions Can Celikbilek* (cc340609@ohio.edu), Sadegh Mirshekarian and Gursel A. Suer, PhD Department of Industrial & Systems

More information

TRANSPORTATION PROBLEMS EXERCISES

TRANSPORTATION PROBLEMS EXERCISES TRANSPORTATION PROBLEMS EXERCISES Vassilis Kostoglou E-mail: vkostogl@it.teithe.gr URL: www.it.teithe.gr/~vkostogl PROBLEM 1 A factory producing aluminum is supplied with bauxite from three mines (01,

More information

A Particle Swarm Optimization Algorithm for Multi-depot Vehicle Routing problem with Pickup and Delivery Requests

A Particle Swarm Optimization Algorithm for Multi-depot Vehicle Routing problem with Pickup and Delivery Requests A Particle Swarm Optimization Algorithm for Multi-depot Vehicle Routing problem with Pickup and Delivery Requests Pandhapon Sombuntham and Voratas Kachitvichayanukul Abstract A particle swarm optimization

More information

An Alternate Method to Matrix Minima Method of Solving Transportation Problem

An Alternate Method to Matrix Minima Method of Solving Transportation Problem Volume 117 No. 1 017, 489-495 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu An Alternate Method to Matrix Minima Method of Solving Transportation

More information

A shift sequence for job scheduling by using Linear programming problem E. Mahalakshmi 1*, S. Akila 2

A shift sequence for job scheduling by using Linear programming problem E. Mahalakshmi 1*, S. Akila 2 A shift sequence for job scheduling by using Linear programming problem E. Mahalakshmi 1*, S. Akila 2 1 Research scholar, Thevanai Ammal College for women (Autonomous) villupuram, 2 Assistant professor,

More information

Solving the Empty Container Problem using Double-Container Trucks to Reduce Congestion

Solving the Empty Container Problem using Double-Container Trucks to Reduce Congestion Solving the Empty Container Problem using Double-Container Trucks to Reduce Congestion Santiago Carvajal scarvaja@usc.edu (424) 333-4929 Daniel J. Epstein Department of Industrial and Systems Engineering

More information

Web Appendix (not for publication)

Web Appendix (not for publication) Web Appendix (not for publication) Online Appendix B. The Model Setup We consider a country consisting of two regions, which we call coast ( c ) and interior ( i ) for exposition. Workers in each region

More information

Introduction to Management Science

Introduction to Management Science Test Item File Introduction to Management Science Bernard W. Taylor III Martha Wilson California State University, Sacramento Upper Saddle River, New Jersey 07458 Contents Chapter 1 Management Science

More information

Scheduling Resources and Costs

Scheduling Resources and Costs Student Version CHAPTER EIGHT Scheduling Resources and Costs McGraw-Hill/Irwin Copyright 2011 by The McGraw-Hill Companies, Inc. All rights reserved. Gannt Chart Developed by Henry Gannt in 1916 is used

More information

Question 2: How do we make decisions about inventory?

Question 2: How do we make decisions about inventory? uestion : How do we make decisions about inventory? Most businesses keep a stock of goods on hand, called inventory, which they intend to sell or use to produce other goods. Companies with a predictable

More information

Linear Programming and Applications

Linear Programming and Applications Linear Programming and Applications (v) LP Applications: Water Resources Problems Objectives To formulate LP problems To discuss the applications of LP in Deciding the optimal pattern of irrigation Water

More information

Manufacturing Resource Planning

Manufacturing Resource Planning Outline Manufacturing Resource Planning MRP The Strategic Importance of Short- Term Scheduling Scheduling Issues Forward and Backward Scheduling Scheduling Criteria Outline Continued Scheduling Process-Focused

More information

Module 04 : Targeting. Lecture 11: PROBLEM TABLE ALGORITHM 1 st Part

Module 04 : Targeting. Lecture 11: PROBLEM TABLE ALGORITHM 1 st Part Module 04 : Targeting Lecture : PROBLEM TABLE ALGORITHM st Part Key words: Problem Table Algorithm, shifted temperature, composite curve, PTA, For a given ΔT min, Composite curves can be used to obtain

More information

QUESTION BANK BCA V SEMESTER BCA-505 OPTIMAZATION TECHNIQUES

QUESTION BANK BCA V SEMESTER BCA-505 OPTIMAZATION TECHNIQUES QUESTION BANK BCA V SEMESTER BCA-0 OPTIMAZATION TECHNIQUES ------ UNIT I ------. A firm manufactures products A, B and C. The profits are Rs., Rs. and Rs. resp. The firm has machines and below is the required

More information

Chapter 3: Planning and Scheduling Lesson Plan

Chapter 3: Planning and Scheduling Lesson Plan Lesson Plan Assumptions and Goals List-Processing Algorithm Optimal Schedules Strange Happenings For All Practical Purposes Mathematical Literacy in Today s World, 8th ed. Critical-Path Schedules Independent

More information

Logistic and production Models

Logistic and production Models i) Supply chain optimization Logistic and production Models In a broad sense, a supply chain may be defined as a network of connected and interdependent organizational units that operate in a coordinated

More information

Learning Objectives. Scheduling. Learning Objectives

Learning Objectives. Scheduling. Learning Objectives Scheduling 16 Learning Objectives Explain what scheduling involves and the importance of good scheduling. Discuss scheduling needs in high-volume and intermediate-volume systems. Discuss scheduling needs

More information