The Transportation Problem

Size: px
Start display at page:

Download "The Transportation Problem"

Transcription

1 11 The Transportation Problem Question 1 The initial allocation of a transportation problem, alongwith the unit cost of transportation from each origin to destination is given below. You are required to arrive at the minimum transportation cost by the Vogel s Approximation method and check for optimality. (Hint : Candidates may consider u 1 = 0 at Row 1 for initial cell evaluation) Requirement Availability (May 2007, 6 Marks) The concept tested in this problem is Degeneracy with respect to the transportation problem. Total of rows and columns = (4 + 5) = 9. Hence, the number of allocations = 9 1 = 8. As the actual number of allocation is 7, a zero allocation is called for. To resolve this, an independent cell with least cost should be chosen. R4C2 has the least cost (cost = 3), but this is not independent. The next least cost cell R4C3 (cost = 5) is independent.

2 The Transportation Problem C1 2 C2 5 C3 6 C4 2 C5 Total R R R R Total Forming Equations through allocated cells Basic equation Setting R1 = 0 other values R1 + C2 = 2 Setting R1 = 0, C2 = 2 R1 + C4 = 6 C4 = 6 R1 + C5 = 2 C5 = 2 R2 + C1 = 9 R2 = 0 R3 + C3 = 3 R3 = 2 R4 + C1 = 9 C1 = 9 R4 + C3 = 5 C3 = 5 R4 + C4 = 6 R4 = 0 Evaluate unallocated cells R1C1 = = 2 R3C1 = = 0 R1C3 = = 3 R3C2 = = 6 R2C2 = = 7 R3C4 = = 7 R2C3 = = 7 R3C5 = = 7 R2C4 = = 3 R4C2 = = 1 R2C5 = = 4 R4C5 = = 9 Since all the evaluation is 0 or +ve, the optimal solution is obtained. Optimal cost = (8 2) + (6 6) + (4 2) + (10 9) + (8 3) + (2 9) + (0 5) + (2 6) =

3 11.3 Advanced Management Accounting = Rs Note: As regards allocation of the zero values, the solution to the above problem is also obtained by allocating the zero value in other independent cells such as R1C3, R2C2, R2C3, R3C1, R3C2, R3C4, R3C5. In such situation there will be one more iteration. Question 2 Goods manufactured at 3 plants, A, B and C are required to be transported to sales outlets X, Y and Z. The unit costs of transporting the goods from the plants to the outlets are given below: Plants Sales outlets A B C Total Demand X Y Z Total supply You are required to: (i) Compute the initial allocation by North-West Corner Rule. (ii) Compute the initial allocation by Vogel s approximation method and check whether it is optional. (iii) State your analysis on the optionality of allocation under North-West corner Rule and Vogel s Approximation method. (10 Marks) (May, 2008) (i) Initial allocation under NW corner rule is as above. Initial cost : 20 3 = = = 80

4 The Transportation Problem 11.4 (ii) 30 3 = = Initial solution by VAM: Initial solution: 20 3 = = = = = Checking for optimality 3 u 1 = u 2 = u 3 = 0 V1 = 3 V2 = 3 V3 = 5 u i + v j

5 11.5 Advanced Management Accounting ij = c ij ( u i + v j ) ij Solution is optimal Conclusion: The solution under VAM is optimal with a zero in R 2 C 2 which means that the cell C 2 R 2 which means that the cell C 2 R 2 can come into solution, which will be another optimal solution. Under NWC rule the initial allocation had C 2 R 2 and the total cost was the same Rs. 460 as the total cost under optimal VAM solution. Thus, in this problem, both methods have yielded the optimal solution under the 1 st allocation. If we do an optimality test for the solution, we will get a zero for ij in C 3 R 2 indicating the other optimal solution which was obtained under VAM. Question 3 State the methods in which initial feasible solution can be arrived at in a transportation problem. (3 Marks) (Nov., 2008) The methods by which initial feasible solution can be arrived at in a transportation model are as under: (i) North West Corner Method. (ii) Least Cost Method (iii) Vogel s Approximation Method (VAM) Question 4 The cost per unit of transporting goods from the factories X, Y, Z to destinations. A, B and C, and the quantities demanded and supplied are tabulated below. As the company is working out the optimum logistics, the Govt.; has announced a fall in oil prices. The revised unit costs are exactly half the costs given in the table. You are required to evaluate the minimum transportation cost. (6 Marks)(June, 2009) Destinations Factories A B C Supply

6 The Transportation Problem 11.6 X Y Z Demand The problem may be treated as an assignment problem. The solution will be the same even if prices are halved. Only at the last stage, calculate the minimum cost and divide it by 2 to account for fall in oil prices. A B C X Y Z Subtracting Row minimum, we get A B C X Y Z A B C Subtracting Column minimum, No of lines required to cut Zeros = 3 Cost / u Units Cost Revised Cost Allocation: X B Y C Z A Minimum cost = 105 Rs. Alternative Solution I Least Cost Method

7 11.7 Advanced Management Accounting X B Y C Z A Test for optimality No. of allocation = 3 No. of rows m =3, no. of column = 3 m + n 1 = = 5 2 very small allocation are done to 2 cells of minimum costs, so that, the following table is got: A B C X e 6 Y Z e 9 m + n 1 = 5 Now testing for optimality

8 The Transportation Problem e 6 e v j u i + v j for unoccupied cells A B C X Y Z u i Diff = Cij (u i + v j ) A B C X Y Z All Δ ij > 0, Hence this is the optimal solution. Original Costs Reduced Costs due to Oil Price X B Y C Z A Total cost of transportation is minimum at Rs.105 Qty. Cost 105

9 11.9 Advanced Management Accounting Alternative Solution II No. of rows + no. of column 1 m + n 1 = 5 No. of allocation = 3 Hence add e to 2 least cost cells so that

10 The Transportation Problem Now m + n 1 = 5 Testing for optimality, u i, v j table A B C u i X 4.5 e 0 Y 3 Z 3 e v j u i + v j for unoccupied cells Cij Δ ij = C ij (u i + v j ) u i +v j

11 11.11 Advanced Management Accounting All Δ ij > 0. Hence the solution is optimal. Qty. Cost/u Total Cost X B Y C Z A Total minimum cost at revised oil prices 105 Question 5 How do you know whether an alternative solution exists for a transportation problem? (4 Marks)(Nov., 2009) The Δ i j matrix = Δ i j = Ci j (u i + v j ) Where c i is the cost matrix and (u i + v j ) is the cell evaluation matrix for allocated cell. The Δ i j matrix has one or more Zero elements, indicating that, if that cell is brought into the solution, the optional cost will not change though the allocation changes. Thus, a Zero element in the Δ i j matrix reveals the possibility of an alternative solution. Question 6 A company has three plants located at A, B and C. The production of these plants is absorbed by four distribution centres located at X, Y, W and Z. the transportation cost per unit has been shown in small cells in the following table: Factories Distribution Centres X Y W Z Supply (Units) A B C Demand (Units) Find the optimum solution of the transportation problem by applying Vogel s Approximation Method. (8 Marks)(Nov., 2010)

12 The Transportation Problem Step 1 : Initial Allocation based on Least cost cells corresponding to highest differences X Y W Z Dummy Total A 2,000 3, ,000 B 1,000 5,000 6,000 C 4,000 2,000 6,000 TOTAL 4,000 4,000 4,500 5, ,000 Step 2 : Δij Matrix values for Unallocated cells X Y W Z Dummy A 0 0 B C All Δij values > 0. Therefore initial allocation is optimal. Step 3 : Optimal Transportation Cost Units Costs involved Total A to Y 2, ,000 A to W 3, ,500 B to W 1, ,000 B to Z 5, ,000 C to X 4, ,000 C to Y 2, ,000 Total minimum cost 1,29,500 Note : Since there are zeroes in the Δij Matrix alternate solutions exist. Question 7 Will the initial solution for a minimization problem obtained by Vogel s Approximation Method and the Least Cost Method be the same? Why? (4 Marks) (May, 2011) The initial solution need not be the same under both methods.

13 11.13 Advanced Management Accounting Vogel s Approximation Method uses the differences between the minimum and the next minimum costs for each row and column. This is the penalty or opportunity cost of not utilising the next best alterative. The highest penalty is given the 1 st preference. This need not be the lowest cost. For example if a row has minimum cost as 3, and the next minimum as 2, penalty is 1; whereas if another row has minimum 4 and next minimum 6, penalty is 2, and this row is given preference. But least cost given preference to the lowest cost cell, irrespective of the next cost. Vogel s Approximation Method will to result in a more optimal solution than least cost. They will be the same only when the maximum penalty and the minimum cost coincide Question 8 The following matrix is a minimization problem for transportation cost. The unit transportation costs are given at the right hand corners of the cells and the ij values are encircled. D1 D2 D3 Supply F F F Deamnd Find the optimum solution (s) and the minimum cost. (5 Marks) (May, 2011) Δ ij values are given for unallocated cells. Hece, no. of allocated cells = 5, which = = no. of columns + no of rows 1. Allocating in other than Δ ij cells. Factory S1 D2 D3 Supply

14 The Transportation Problem This solution is optional since Δ ij are non-ve. For the other optional solution, which exists since Δ ij = 0 at R 3 C 1, this cell should be brought in with a loop : R 3, C 1 R 1 C 1 R 1 C 3 R 3 C 3. Working Notes: Step I : R 1 C 1 (Minimum of 300, 500) Step II : R 2 C 2 (Minimum of 300, 400) Step III : R 1 C 2 balance of C 2 total : 100, R 1 Total = 100 Step IV : R 1 C (balance of C 3 total = 200) Step V : R 3 C Solution I Solution II Solution I Solution II Cost: 3 х 300 = х 200 = х 100 = х 100 = х 100 = х 200 = х 300 = х 300 = х 200 = х 100 = х 100 = 400 Minimum Cost

15 11.15 Advanced Management Accounting Question 9 The following table gives the unit transportation costs and the quantities demanded/supplied at different locations for a minimization problem: Supply Demand C 1 C 2 C 3 C 4 Total Units R R R Total Units You are required to find out which cell gets the 3rd allocation in the initial basic feasible solution under each of the following methods and to give the cell reference, cost per unit of that cell and the quantity allocated to that cell : (i) North West Corner Rule (ii) Vogel's Approximation Method (iii) Least Cost Method (Candidates may use the standard notation of C i R j for cell reference.( e.g. C 2 R 3 means the cell at the intersection of Column 2 and Row 3 ) (Note: The full solution is not required to be worked out). (5 Marks)(May, 2012) Sl. No Method Cell Reference Cost/unit Quantity I II III i) North West Corner Rule C 2 R ,000 ii) Vogel s method C 3 R ,000 C 1 R ,000 iii) Least Cost Method C 1 R ,000 Question 10 In a transportation problem for cost minimization, there are 4 rows indicating quantities demanded and this totals up to 1,200 units. There are 4 columns giving quantities supplied. This totals up to 1,400 units. What is the condition for a solution to be degenerate? (3 Marks)(May, 2012) or

16 The Transportation Problem The condition for degeneracy is that the number of allocations in a solution is less than m+n-1. The given problem is an unbalanced situation and hence a dummy row is to be added, since the Column quantity is greater than that of the Row quantity. The total number of Rows and Columns then = 9 i.e. (5+4). Therefore, m+n-1 = 8, i.e. if the number of allocations is less than 8, then degeneracy would occur. Question 11 Explain the term 'Degeneracy' in the context of a transportation problem. How can this be solved? (5 Marks)(Nov., 2012) A transportation problem s solution has m+n-1 basic variables, (where m,n are the number of rows and columns) which means that the number of occupied cells in such a solution is one less than the number of rows and number of columns. When the number of occupied cells in a solution is less than m+n-1, the solution is called a degenerate solution. Such a situation is handled by introducing an infinitesimally small allocation e in the least cost and independent cell. If the number of occupied cells < m+n-1 by one, then only one e needs to be introduced. If the number of occupied cells is less by more than one, to the extent of shortage, e s will have to be introduced till the condition that no. of occupied cells = m+n-1. For e.g. if no. of occupied cells in a solution is 7 and we have m+n-1 = 9, then, we have to introduce two quantities of e, say e 1 and e 2 in 2 of the least cost independent cells. Degeneracy occurs because in any particular allocation (earlier than the last allocation), the row and column totals get simultaneously fulfilled. (In the last allocation, it is always that row and column get fulfilled). Then, we have a degeneracy by one number, i.e. no. of occupied cells +1= m+n-1. We need to put one e. In the subsequent allocation, if again row and column totals get fulfilled simultaneously, again there will be a shortage of occupied cells and another e will be required. Due to this concept, an assignment problem, solved by transportation technique taking demand quantity = supply quantity = 1 in every row and column will require an e for each allocation other than the last one. For e.g. in a 5 x 5 assignment problem, there are 4 allocations other than the last one.therefore, 4 e s will be required.i.e. m + n -1 will be 5+5-1, =9, whereas, the no. of occupied cells will be 5.To resolve the degeneracy, we will need 4 e s. The e has to be placed in the least cost independent cell, for arriving at the optimal solution as early as possible. If, by mistake, we place e in the second least cost but independent cell, after the u i, v j step, the e will be shifted to the least cost independent cell, thereby necessitating one more iteration. This is similar to the simplex table. If we bring in a wrong

17 11.17 Advanced Management Accounting variable by mistake, it will go out in the next iteration. The only thing is that the solution will be reached later. Question 12 XYZ Company has three plants and four warehouses. The supply and demand in units and the corresponding transportation costs are given. The table below shows the details taken from the solution procedure of the transportation problem : WAREHOURSES I II III IV Supply A Plants B C Demand the following questions. Give brief reasons: (i) Is this solution feasible? (ii) Is this solution degenerate? (iii) Is this solution optimum? (8 Marks)(May,2013) (i) Is this solution feasible? A necessary and sufficient condition for the existence of a feasible solution to the transportation problem is that (ii) m n a i b j i 1 j 1 Where a i = quantity of product available at origin i. b j = quantity of product available at origin j. In other words, the total capacity (or supply) must equal total requirement (or demand) As the supply 55 units ( ) equals demand 55 units ( ), a feasible solution to the problem exists. Is this solution degenerate?

18 The Transportation Problem When the number of positive allocations at any stage of the feasible solution is less than the required number (rows + columns -1), the solution is said to be degenerate solution. In given solution total allocated cells are 6 which are equal to (rows + columns -1). Therefore, the initial basic solution is not a degenerate solution. (iii) Is this solution optimum? Test of Optimality: (u i +v j ) matrix for allocated cells u i v j (u i +v j ) matrix for unallocated cells u i v j ij = C ij (u i +v j ) matrix Since, all cells values in ij = C ij (u i +v j ) matrix are non- negative, hence the solution provided by XYZ Company is optimum. It may be noted that zero opportunity cost in cell (B, III) indicates a case of alternative optimum solution. Question 13 Define the following terms in relation to a transportation problem: (i) Degeneracy (ii) Prohibited routes (4 Marks)(Nov., 2013) 7

19 11.19 Advanced Management Accounting (i) Degeneracy: A transportation problem s solution has m+n 1 basic variables, (where m,n are the number of rows and columns) which means that the number of occupied cells in such a solution is one less than the number of rows and number of columns. When the number of occupied cells in a solution is less than m+n 1, the solution is called a degenerate solution. Such a situation is handled by introducing an infinitesimally small allocation e in the least cost and independent cell. (ii) Prohibited Routes: Sometimes in a given transportation problem, some routes may not be available. There could be several reasons for this such as bad road conditions or strike etc. In such situations, there is a restriction on the route available for transportation. To handle such type of a situation, a very large cost (or a negative profit for the maximization problem) represented by or M is assigned to each of such routes which are not available. Due to assignment of very large cost, such routes would automatically be eliminated in the final solution. The problem is the solved in its usual way. Question 14 Will the solution for a minimization problem obtained by Vogel's Approximation Method and Least Cost Method be the same? Why? (4 Marks) (May, 2014) The initial solution need not be the same under both methods. Vogel s Approximation Method (VAM) uses the differences between the minimum and the next minimum costs for each row and column. This is the penalty or opportunity cost of not utilising the next best alternative. The highest penalty is given the 1 st preference. This need not be the lowest cost. For example if a row has minimum cost as 2, and the next minimum as 3, penalty is 1; whereas if another row has minimum 4 and next minimum 6, penalty is 2, and this row is given preference. But Least Cost Method gives preference to the lowest cost cell, irrespective of the next cost. Solution obtained using Vogel s Approximation Method is more optimal than Least Cost Method. Initial solution will be same only when the maximum penalty and the minimum cost coincide. Question 15 In a 3 x 4 transportation problem for minimizing costs, will the R 2 C 1 cell (at the intersection of the 2 nd row and 1 st column) always figure in the initial solution by the North West Corner Rule? Why? (4 Marks) (May, 2014)

20 The Transportation Problem The Initial solution obtained by the North-West Corner Rule in transportation need not always contain the R 2 C 1 cell. In the North-West Corner Rule the first allocation is made at R 1 C 1 cell and then it only moves towards R 2 C 1 cell when the resources at the first row i.e. R 1 is exhausted first than the resources of first column i.e. C 1. On the contrary if resources at first column i.e. C 1 is exhausted first then the next allocation will be at R 1 C 2. For example the resource availability at first row (R 1 ) is 1,500 units and the demand in first column (C 1 ) is 1,000 units. In this case resource availability of first row (R 1 ) will be exhausted to the extent of the demand in first column (C 1 ) first and then the remaining resource availability at first row (R 1 ) will be used to meet the demand of the second column (C 2 ). In this example cell R 2 C 1 will not come in initial solution obtained by the North-West Corner Rule. Question 16 In a transport problem for cost minimization, there are 4 rows indicating quantities demanded and these totals up to 1800 units. There are 4 columns giving quantities supplied and these totals up to 2,100 units. What is the condition for a solution to be degenerate? (4 Marks) (November, 2014) The condition for degeneracy is that the number of allocations in a solution is less than m+n-1. The given problem is an unbalanced situation and hence a dummy row is to be added, since the column quantity is greater than that of the row quantity. The total number of rows and columns will be 9 i.e. (5 rows and 4 columns). Therefore, m+n-1 = 8, i.e. if the number of allocations is less than 8, then degeneracy would occur.

The Transportation Problem

The Transportation Problem CHAPTER 12 The Transportation Problem Basic Concepts 1. Transportation Problem: BASIC CONCEPTS AND FORMULA This type of problem deals with optimization of transportation cost in a distribution scenario

More information

Chapter 7 TRANSPORTATION PROBLEM

Chapter 7 TRANSPORTATION PROBLEM Chapter 7 TRANSPORTATION PROBLEM Chapter 7 Transportation Transportation problem is a special case of linear programming which aims to minimize the transportation cost to supply goods from various sources

More information

UNIT 4 TRANSPORTATION PROBLEM

UNIT 4 TRANSPORTATION PROBLEM UNIT 4 TRANSPORTATION PROLEM Structure 4.1 Introduction Objectives 4.2 Mathematical Formulation of the Transportation Problem 4.3 Methods of Finding Initial asic Feasible Solution North-West orner Rule

More information

OPERATIONS RESEARCH. Transportation and Assignment Problems

OPERATIONS RESEARCH. Transportation and Assignment Problems OPERATIONS RESEARCH Chapter 2 Transportation and Assignment Problems Prof. Bibhas C. Giri Department of Mathematics Jadavpur University Kolkata, India Email: bcgiri.jumath@gmail.com MODULE - 2: Optimality

More information

TRANSPORTATION PROBLEMS

TRANSPORTATION PROBLEMS 63 TRANSPORTATION PROBLEMS 63.1 INTRODUCTION A scooter production company produces scooters at the units situated at various places (called origins) and supplies them to the places where the depot (called

More information

TRANSPORTATION & NETWORK PROBLEMS

TRANSPORTATION & NETWORK PROBLEMS TRANSPORTATION & NETWORK PROBLEMS Transportation Problems Problem: moving output from multiple sources to multiple destinations. The objective is to minimise costs (maximise profits). Network Representation

More information

OPERATIONS RESEARCH. Transportation and Assignment Problems

OPERATIONS RESEARCH. Transportation and Assignment Problems OPERATIONS RESEARCH Chapter 2 Transportation and Assignment Problems Prof. Bibhas C. Giri Department of Mathematics Jadavpur University Kolkata, India Email: bcgiri.jumath@gmail.com 1.0 Introduction In

More information

Duality in LPP Every LPP called the primal is associated with another LPP called dual. Either of the problems is primal with the other one as dual. The optimal solution of either problem reveals the information

More information

Transportation Problem

Transportation Problem Transportation Problem. Production costs at factories F, F, F and F 4 are Rs.,, and respectively. The production capacities are 0, 70, 40 and 0 units respectively. Four stores S, S, S and S 4 have requirements

More information

W P 1 30 / 10 / P 2 25 / 15 / P 3 20 / / 0 20 / 10 / 0 35 / 20 / 0

W P 1 30 / 10 / P 2 25 / 15 / P 3 20 / / 0 20 / 10 / 0 35 / 20 / 0 11 P 1 and W 1 with shipping cost. The column total (i.e. market requirement) corresponding to this cell is 2 while the row total (Plant capacity) is. So we allocate 2 units to this cell. Not the market

More information

Example: 1. In this chapter we will discuss the transportation and assignment problems which are two special kinds of linear programming.

Example: 1. In this chapter we will discuss the transportation and assignment problems which are two special kinds of linear programming. Ch. 4 THE TRANSPORTATION AND ASSIGNMENT PROBLEMS In this chapter we will discuss the transportation and assignment problems which are two special kinds of linear programming. deals with transporting goods

More information

MULTIPLE CHOICE QUESTIONS DECISION SCIENCE

MULTIPLE CHOICE QUESTIONS DECISION SCIENCE MULTIPLE CHOICE QUESTIONS DECISION SCIENCE 1. Decision Science approach is a. Multi-disciplinary b. Scientific c. Intuitive 2. For analyzing a problem, decision-makers should study a. Its qualitative aspects

More information

Fundamentals of Operations Research. Prof. G. Srinivasan. Indian Institute of Technology Madras. Lecture No. # 15

Fundamentals of Operations Research. Prof. G. Srinivasan. Indian Institute of Technology Madras. Lecture No. # 15 Fundamentals of Operations Research Prof. G. Srinivasan Indian Institute of Technology Madras Lecture No. # 15 Transportation Problem - Other Issues Assignment Problem - Introduction In the last lecture

More information

Linear Programming Applications. Transportation Problem

Linear Programming Applications. Transportation Problem Linear Programming Applications Transportation Problem 1 Introduction Transportation problem is a special problem of its own structure. Planning model that allocates resources, machines, materials, capital

More information

CHAPTER SOLVING MULTI-OBJECTIVE TRANSPORTATION PROBLEM USING FUZZY PROGRAMMING TECHNIQUE-PARALLEL METHOD 40 3.

CHAPTER SOLVING MULTI-OBJECTIVE TRANSPORTATION PROBLEM USING FUZZY PROGRAMMING TECHNIQUE-PARALLEL METHOD 40 3. CHAPTER - 3 40 SOLVING MULTI-OBJECTIVE TRANSPORTATION PROBLEM USING FUZZY PROGRAMMING TECHNIQUE-PARALLEL METHOD 40 3.1 INTRODUCTION 40 3.2 MULTIOBJECTIVE TRANSPORTATION PROBLEM 41 3.3 THEOREMS ON TRANSPORTATION

More information

M.SC. MATHEMATICS - II YEAR

M.SC. MATHEMATICS - II YEAR MANONMANIAM SUNDARANAR UNIVERSITY DIRECTORATE OF DISTANCE & CONTINUING EDUCATION TIRUNELVELI 627012, TAMIL NADU M.SC. MATHEMATICS - II YEAR DKM24 - OPERATIONS RESEARCH (From the academic year 2016-17)

More information

Dr. S. Bourazza Math-473 Jazan University Department of Mathematics

Dr. S. Bourazza Math-473 Jazan University Department of Mathematics Dr. Said Bourazza Department of Mathematics Jazan University 1 P a g e Contents: Chapter 0: Modelization 3 Chapter1: Graphical Methods 7 Chapter2: Simplex method 13 Chapter3: Duality 36 Chapter4: Transportation

More information

Operations Research: Introduction. Concept of a Model

Operations Research: Introduction. Concept of a Model Origin and Development Features Operations Research: Introduction Term or coined in 1940 by Meclosky & Trefthan in U.K. came into existence during World War II for military projects for solving strategic

More information

II BSc(Information Technology)-[ ] Semester-III Allied:Computer Based Optimization Techniques-312C Multiple Choice Questions.

II BSc(Information Technology)-[ ] Semester-III Allied:Computer Based Optimization Techniques-312C Multiple Choice Questions. Dr.G.R.Damodaran College of Science (Autonomous, affiliated to the Bharathiar University, recognized by the UGC)Re-accredited at the 'A' Grade Level by the NAAC and ISO 9001:2008 Certified CRISL rated

More information

The Assignment Problem

The Assignment Problem CHAPTER 12 The Assignment Problem Basic Concepts Assignment Algorithm The Assignment Problem is another special case of LPP. It occurs when m jobs are to be assigned to n facilities on a one-to-one basis

More information

Transportation Simplex: Initial BFS 03/20/03 page 1 of 12

Transportation Simplex: Initial BFS 03/20/03 page 1 of 12 Dennis L. ricker Dept of Mechanical & Industrial Engineering The University of Iowa & Dept of usiness Lithuania hristian ollege Transportation Simplex: Initial FS 0/0/0 page of Obtaining an Initial asic

More information

UNIT-4 Chapter6 Linear Programming

UNIT-4 Chapter6 Linear Programming UNIT-4 Chapter6 Linear Programming Linear Programming 6.1 Introduction Operations Research is a scientific approach to problem solving for executive management. It came into existence in England during

More information

Deterministic Operations Research, ME 366Q and ORI 391 Chapter 2: Homework #2 Solutions

Deterministic Operations Research, ME 366Q and ORI 391 Chapter 2: Homework #2 Solutions Deterministic Operations Research, ME 366Q and ORI 391 Chapter 2: Homework #2 Solutions 11. Consider the following linear program. Maximize z = 6x 1 + 3x 2 subject to x 1 + 2x 2 2x 1 + x 2 20 x 1 x 2 x

More information

2. Linear Programming Problem

2. Linear Programming Problem . Linear Programming Problem. Introduction to Linear Programming Problem (LPP). When to apply LPP or Requirement for a LPP.3 General form of LPP. Assumptions in LPP. Applications of Linear Programming.6

More information

The Transportation Problem. Experience the Joy! Feel the Excitement! Share in the Pleasure!

The Transportation Problem. Experience the Joy! Feel the Excitement! Share in the Pleasure! The Transportation Problem Experience the Joy! Feel the Excitement! Share in the Pleasure! The Problem A company manufactures a single product at each of m factories. i has a capacity of S i per month.

More information

II. MATHEMATICAL FORM OF TRANSPORTATION PROBLEM The LP problem is as follows. Minimize Z = C X. Subject to the constraints X d For all j

II. MATHEMATICAL FORM OF TRANSPORTATION PROBLEM The LP problem is as follows. Minimize Z = C X. Subject to the constraints X d For all j www.ijraset.com Volume Issue X, October 216 A New Technique to Obtain Initial Basic Feasible Solution for the Transportation Problem A. Seethalakshmy 1, N. Srinivasan 2 1 Research Scholar, Department of

More information

ST. JOSEPH S COLLEGE OF ARTS & SCIENCE (AUTONOMOUS) CUDDALORE-1

ST. JOSEPH S COLLEGE OF ARTS & SCIENCE (AUTONOMOUS) CUDDALORE-1 ST. JOSEPH S COLLEGE OF ARTS & SCIENCE (AUTONOMOUS) CUDDALORE-1 SUB:OPERATION RESEARCH CLASS: III B.SC SUB CODE:EMT617S SUB INCHARGE:S.JOHNSON SAVARIMUTHU 2 MARKS QUESTIONS 1. Write the general model of

More information

Lecture 14 Transportation Algorithm. October 9, 2009

Lecture 14 Transportation Algorithm. October 9, 2009 Transportation Algorithm October 9, 2009 Outline Lecture 14 Revisit the transportation problem Simplex algorithm for the balanced problem Basic feasible solutions Selection of the initial basic feasible

More information

56:171 Operations Research Fall 1998

56:171 Operations Research Fall 1998 56:171 Operations Research Fall 1998 Quiz Solutions D.L.Bricker Dept of Mechanical & Industrial Engineering University of Iowa 56:171 Operations Research Quiz

More information

Review Questions, Final Exam

Review Questions, Final Exam Review Questions, Final Exam A few general questions 1. What does the Representation Theorem say (in linear programming)? 2. What is the Fundamental Theorem of Linear Programming? 3. What is the main idea

More information

UNIVERSITY of LIMERICK

UNIVERSITY of LIMERICK UNIVERSITY of LIMERICK OLLSCOIL LUIMNIGH Department of Mathematics & Statistics Faculty of Science and Engineering END OF SEMESTER ASSESSMENT PAPER MODULE CODE: MS4303 SEMESTER: Spring 2018 MODULE TITLE:

More information

February 17, Simplex Method Continued

February 17, Simplex Method Continued 15.053 February 17, 2005 Simplex Method Continued 1 Today s Lecture Review of the simplex algorithm. Formalizing the approach Alternative Optimal Solutions Obtaining an initial bfs Is the simplex algorithm

More information

To Obtain Initial Basic Feasible Solution Physical Distribution Problems

To Obtain Initial Basic Feasible Solution Physical Distribution Problems Global Journal of Pure and Applied Mathematics. ISSN 0973-1768 Volume 13, Number 9 (2017), pp. 4671-4676 Research India Publications http://www.ripublication.com To Obtain Initial Basic Feasible Solution

More information

International Journal of Mathematical Archive-4(11), 2013, Available online through ISSN

International Journal of Mathematical Archive-4(11), 2013, Available online through   ISSN International Journal of Mathematical Archive-(),, 71-77 Available online through www.ijma.info ISSN 2229 06 A NEW TYPE OF TRANSPORTATION PROBLEM USING OBJECT ORIENTED MODEL R. Palaniyappa 1* and V. Vinoba

More information

Programmers A B C D Solution:

Programmers A B C D Solution: P a g e Q: A firm has normally distributed forecast of usage with MAD=0 units. It desires a service level, which limits the stock, out to one order cycle per year. Determine Standard Deviation (SD), if

More information

9.5 THE SIMPLEX METHOD: MIXED CONSTRAINTS

9.5 THE SIMPLEX METHOD: MIXED CONSTRAINTS SECTION 9.5 THE SIMPLEX METHOD: MIXED CONSTRAINTS 557 9.5 THE SIMPLEX METHOD: MIXED CONSTRAINTS In Sections 9. and 9., you looked at linear programming problems that occurred in standard form. The constraints

More information

Examples of linear systems and explanation of the term linear. is also a solution to this equation.

Examples of linear systems and explanation of the term linear. is also a solution to this equation. . Linear systems Examples of linear systems and explanation of the term linear. () ax b () a x + a x +... + a x b n n Illustration by another example: The equation x x + 5x 7 has one solution as x 4, x

More information

CMA Students Newsletter (For Intermediate Students)

CMA Students Newsletter (For Intermediate Students) Special Edition on Assignment Problem An assignment problem is a special case of transportation problem, where the objective is to assign a number of resources to an equal number of activities so as to

More information

56:171 Operations Research Midterm Exam - October 26, 1989 Instructor: D.L. Bricker

56:171 Operations Research Midterm Exam - October 26, 1989 Instructor: D.L. Bricker 56:171 Operations Research Midterm Exam - October 26, 1989 Instructor: D.L. Bricker Answer all of Part One and two (of the four) problems of Part Two Problem: 1 2 3 4 5 6 7 8 TOTAL Possible: 16 12 20 10

More information

Linear Programming. H. R. Alvarez A., Ph. D. 1

Linear Programming. H. R. Alvarez A., Ph. D. 1 Linear Programming H. R. Alvarez A., Ph. D. 1 Introduction It is a mathematical technique that allows the selection of the best course of action defining a program of feasible actions. The objective of

More information

Slack Variable. Max Z= 3x 1 + 4x 2 + 5X 3. Subject to: X 1 + X 2 + X x 1 + 4x 2 + X X 1 + X 2 + 4X 3 10 X 1 0, X 2 0, X 3 0

Slack Variable. Max Z= 3x 1 + 4x 2 + 5X 3. Subject to: X 1 + X 2 + X x 1 + 4x 2 + X X 1 + X 2 + 4X 3 10 X 1 0, X 2 0, X 3 0 Simplex Method Slack Variable Max Z= 3x 1 + 4x 2 + 5X 3 Subject to: X 1 + X 2 + X 3 20 3x 1 + 4x 2 + X 3 15 2X 1 + X 2 + 4X 3 10 X 1 0, X 2 0, X 3 0 Standard Form Max Z= 3x 1 +4x 2 +5X 3 + 0S 1 + 0S 2

More information

THREE-DIMENS IONAL TRANSPORTATI ON PROBLEM WITH CAPACITY RESTRICTION *

THREE-DIMENS IONAL TRANSPORTATI ON PROBLEM WITH CAPACITY RESTRICTION * NZOR volume 9 number 1 January 1981 THREE-DIMENS IONAL TRANSPORTATI ON PROBLEM WITH CAPACITY RESTRICTION * S. MISRA AND C. DAS DEPARTMENT OF MATHEMATICS, REGIONAL ENGINEERING COLLEGE, ROURKELA - 769008,

More information

Concept and Definition. Characteristics of OR (Features) Phases of OR

Concept and Definition. Characteristics of OR (Features) Phases of OR Concept and Definition Operations research signifies research on operations. It is the organized application of modern science, mathematics and computer techniques to complex military, government, business

More information

Special cases of linear programming

Special cases of linear programming Special cases of linear programming Infeasible solution Multiple solution (infinitely many solution) Unbounded solution Degenerated solution Notes on the Simplex tableau 1. The intersection of any basic

More information

Balance An Unbalanced Transportation Problem By A Heuristic approach

Balance An Unbalanced Transportation Problem By A Heuristic approach International Journal of Mathematics And Its Applications Vol.1 No.1 (2013), pp.12-18(galley Proof) ISSN:(online) Balance An Unbalanced Transportation Problem By A Heuristic approach Nigus Girmay and Tripti

More information

56:270 Final Exam - May

56:270  Final Exam - May @ @ 56:270 Linear Programming @ @ Final Exam - May 4, 1989 @ @ @ @ @ @ @ @ @ @ @ @ @ @ Select any 7 of the 9 problems below: (1.) ANALYSIS OF MPSX OUTPUT: Please refer to the attached materials on the

More information

OPERATIONS RESEARCH. Linear Programming Problem

OPERATIONS RESEARCH. Linear Programming Problem OPERATIONS RESEARCH Chapter 1 Linear Programming Problem Prof. Bibhas C. Giri Department of Mathematics Jadavpur University Kolkata, India Email: bcgiri.jumath@gmail.com MODULE - 2: Simplex Method for

More information

Advanced Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras

Advanced Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Advanced Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Lecture - 3 Simplex Method for Bounded Variables We discuss the simplex algorithm

More information

ECE 307 Techniques for Engineering Decisions

ECE 307 Techniques for Engineering Decisions ECE 7 Techniques for Engineering Decisions Introduction to the Simple Algorithm George Gross Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign ECE 7 5 9 George

More information

Standard Form An LP is in standard form when: All variables are non-negativenegative All constraints are equalities Putting an LP formulation into sta

Standard Form An LP is in standard form when: All variables are non-negativenegative All constraints are equalities Putting an LP formulation into sta Chapter 4 Linear Programming: The Simplex Method An Overview of the Simplex Method Standard Form Tableau Form Setting Up the Initial Simplex Tableau Improving the Solution Calculating the Next Tableau

More information

SEN301 OPERATIONS RESEARCH I LECTURE NOTES

SEN301 OPERATIONS RESEARCH I LECTURE NOTES SEN30 OPERATIONS RESEARCH I LECTURE NOTES SECTION II (208-209) Y. İlker Topcu, Ph.D. & Özgür Kabak, Ph.D. Acknowledgements: We would like to acknowledge Prof. W.L. Winston's "Operations Research: Applications

More information

Lecture 2: The Simplex method

Lecture 2: The Simplex method Lecture 2 1 Linear and Combinatorial Optimization Lecture 2: The Simplex method Basic solution. The Simplex method (standardform, b>0). 1. Repetition of basic solution. 2. One step in the Simplex algorithm.

More information

A New Method for Solving Bi-Objective Transportation Problems

A New Method for Solving Bi-Objective Transportation Problems Australian Journal of Basic and Applied Sciences, 5(10): 67-74, 2011 ISSN 1991-8178 A New Method for Solving Bi-Objective Transportation Problems P. Pandian and D. Anuradha Department of Mathematics, School

More information

Linear Programming CHAPTER 11 BASIC CONCEPTS AND FORMULA. Basic Concepts 1. Linear Programming

Linear Programming CHAPTER 11 BASIC CONCEPTS AND FORMULA. Basic Concepts 1. Linear Programming CHAPTER 11 Linear Programming Basic Concepts 1. Linear Programming BASIC CONCEPTS AND FORMULA Linear programming is a mathematical technique for determining the optimal allocation of re- sources nd achieving

More information

Operations Research. Unbalanced transportation problem.

Operations Research. Unbalanced transportation problem. Operations Research. and properties of solutions In the previous lesson, the two special types of solutions of transportation problems (degenerate and alternative) mentioned. However, since both of these

More information

2-Vehicle Cost Varying Transportation Problem

2-Vehicle Cost Varying Transportation Problem Journal of Uncertain Systems Vol.8, No.1, pp.44-7, 14 Online at: www.jus.org.uk -Vehicle Cost Varying Transportation Problem Arpita Panda a,, Chandan Bikash Das b a Department of Mathematics, Sonakhali

More information

4.6 Linear Programming duality

4.6 Linear Programming duality 4.6 Linear Programming duality To any minimization (maximization) LP we can associate a closely related maximization (minimization) LP Different spaces and objective functions but in general same optimal

More information

Decision Mathematics D2 Advanced/Advanced Subsidiary. Monday 1 June 2009 Morning Time: 1 hour 30 minutes

Decision Mathematics D2 Advanced/Advanced Subsidiary. Monday 1 June 2009 Morning Time: 1 hour 30 minutes Paper Reference(s) 6690/01 Edexcel GCE Decision Mathematics D2 Advanced/Advanced Subsidiary Monday 1 June 2009 Morning Time: 1 hour 30 minutes Materials required for examination Nil Items included with

More information

Introduction to Operations Research. Linear Programming

Introduction to Operations Research. Linear Programming Introduction to Operations Research Linear Programming Solving Optimization Problems Linear Problems Non-Linear Problems Combinatorial Problems Linear Problems Special form of mathematical programming

More information

TRANSPORTATION PROBLEMS

TRANSPORTATION PROBLEMS Chapter 6 TRANSPORTATION PROBLEMS 61 Transportation Model Transportation models deal with the determination of a minimum-cost plan for transporting a commodity from a number of sources to a number of destinations

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 Lecture - 13 Multiple Item Inventory - Constraint on Money Value, Space,

More information

Bachelor s Degree Programme Operations Research (Valid from 1st January, 2012 to 30th November, 2012.)

Bachelor s Degree Programme Operations Research (Valid from 1st January, 2012 to 30th November, 2012.) AOR-01 ASSIGNMENT BOOKLET Bachelor s Degree Programme Operations Research (Valid from 1st January, 2012 to 30th November, 2012.) It is compulsory to submit the assignment before filling in the exam form.

More information

Introduction to Operations Research

Introduction to Operations Research Introduction to Operations Research Linear Programming Solving Optimization Problems Linear Problems Non-Linear Problems Combinatorial Problems Linear Problems Special form of mathematical programming

More information

3. THE SIMPLEX ALGORITHM

3. THE SIMPLEX ALGORITHM Optimization. THE SIMPLEX ALGORITHM DPK Easter Term. Introduction We know that, if a linear programming problem has a finite optimal solution, it has an optimal solution at a basic feasible solution (b.f.s.).

More information

Solving the Transportation Problem Using Fuzzy Modified Distribution Method

Solving the Transportation Problem Using Fuzzy Modified Distribution Method Solving the Transportation Problem Using Fuzzy Modified Distribution Method S.Nareshkumar 1, S.Kumaraghuru 2 1 SriGuru Institute of Technology,Coimbatore. 2 Chikkanna Government Arts College, Tirupur.

More information

MS-E2140. Lecture 1. (course book chapters )

MS-E2140. Lecture 1. (course book chapters ) Linear Programming MS-E2140 Motivations and background Lecture 1 (course book chapters 1.1-1.4) Linear programming problems and examples Problem manipulations and standard form problems Graphical representation

More information

LINEAR PROGRAMMING BASIC CONCEPTS AND FORMULA

LINEAR PROGRAMMING BASIC CONCEPTS AND FORMULA CHAPTER 11 LINEAR PROGRAMMING Basic Concepts 1. Linear Programming BASIC CONCEPTS AND FORMULA Linear programming is a mathematical technique for determining the optimal allocation of re- sources nd achieving

More information

Optimisation. 3/10/2010 Tibor Illés Optimisation

Optimisation. 3/10/2010 Tibor Illés Optimisation Optimisation Lectures 3 & 4: Linear Programming Problem Formulation Different forms of problems, elements of the simplex algorithm and sensitivity analysis Lecturer: Tibor Illés tibor.illes@strath.ac.uk

More information

Simplex tableau CE 377K. April 2, 2015

Simplex tableau CE 377K. April 2, 2015 CE 377K April 2, 2015 Review Reduced costs Basic and nonbasic variables OUTLINE Review by example: simplex method demonstration Outline Example You own a small firm producing construction materials for

More information

IE 5531: Engineering Optimization I

IE 5531: Engineering Optimization I IE 5531: Engineering Optimization I Lecture 7: Duality and applications Prof. John Gunnar Carlsson September 29, 2010 Prof. John Gunnar Carlsson IE 5531: Engineering Optimization I September 29, 2010 1

More information

Systems Analysis in Construction

Systems Analysis in Construction Systems Analysis in Construction CB312 Construction & Building Engineering Department- AASTMT by A h m e d E l h a k e e m & M o h a m e d S a i e d 3. Linear Programming Optimization Simplex Method 135

More information

Study Unit 3 : Linear algebra

Study Unit 3 : Linear algebra 1 Study Unit 3 : Linear algebra Chapter 3 : Sections 3.1, 3.2.1, 3.2.5, 3.3 Study guide C.2, C.3 and C.4 Chapter 9 : Section 9.1 1. Two equations in two unknowns Algebraically Method 1: Elimination Step

More information

The Dual Simplex Algorithm

The Dual Simplex Algorithm p. 1 The Dual Simplex Algorithm Primal optimal (dual feasible) and primal feasible (dual optimal) bases The dual simplex tableau, dual optimality and the dual pivot rules Classical applications of linear

More information

D1 D2 D3 - 50

D1 D2 D3 - 50 CSE 8374 QM 721N Network Flows: Transportation Problem 1 Slide 1 Slide 2 The Transportation Problem The uncapacitated transportation problem is one of the simplest of the pure network models, provides

More information

56:171 Fall 2002 Operations Research Quizzes with Solutions

56:171 Fall 2002 Operations Research Quizzes with Solutions 56:7 Fall Operations Research Quizzes with Solutions Instructor: D. L. Bricker University of Iowa Dept. of Mechanical & Industrial Engineering Note: In most cases, each quiz is available in several versions!

More information

Exam 3 Review Math 118 Sections 1 and 2

Exam 3 Review Math 118 Sections 1 and 2 Exam 3 Review Math 118 Sections 1 and 2 This exam will cover sections 5.3-5.6, 6.1-6.3 and 7.1-7.3 of the textbook. No books, notes, calculators or other aids are allowed on this exam. There is no time

More information

The Simplex Method of Linear Programming

The Simplex Method of Linear Programming The Simplex Method of Linear Programming Online Tutorial 3 Tutorial Outline CONVERTING THE CONSTRAINTS TO EQUATIONS SETTING UP THE FIRST SIMPLEX TABLEAU SIMPLEX SOLUTION PROCEDURES SUMMARY OF SIMPLEX STEPS

More information

Chap6 Duality Theory and Sensitivity Analysis

Chap6 Duality Theory and Sensitivity Analysis Chap6 Duality Theory and Sensitivity Analysis The rationale of duality theory Max 4x 1 + x 2 + 5x 3 + 3x 4 S.T. x 1 x 2 x 3 + 3x 4 1 5x 1 + x 2 + 3x 3 + 8x 4 55 x 1 + 2x 2 + 3x 3 5x 4 3 x 1 ~x 4 0 If we

More information

OPRE 6201 : 3. Special Cases

OPRE 6201 : 3. Special Cases OPRE 6201 : 3. Special Cases 1 Initialization: The Big-M Formulation Consider the linear program: Minimize 4x 1 +x 2 3x 1 +x 2 = 3 (1) 4x 1 +3x 2 6 (2) x 1 +2x 2 3 (3) x 1, x 2 0. Notice that there are

More information

Lecture 5 Simplex Method. September 2, 2009

Lecture 5 Simplex Method. September 2, 2009 Simplex Method September 2, 2009 Outline: Lecture 5 Re-cap blind search Simplex method in steps Simplex tableau Operations Research Methods 1 Determining an optimal solution by exhaustive search Lecture

More information

THE UNIVERSITY OF HONG KONG DEPARTMENT OF MATHEMATICS. Operations Research I

THE UNIVERSITY OF HONG KONG DEPARTMENT OF MATHEMATICS. Operations Research I LN/MATH2901/CKC/MS/2008-09 THE UNIVERSITY OF HONG KONG DEPARTMENT OF MATHEMATICS Operations Research I Definition (Linear Programming) A linear programming (LP) problem is characterized by linear functions

More information

Econ 172A, Fall 2012: Final Examination (I) 1. The examination has seven questions. Answer them all.

Econ 172A, Fall 2012: Final Examination (I) 1. The examination has seven questions. Answer them all. Econ 172A, Fall 12: Final Examination (I) Instructions. 1. The examination has seven questions. Answer them all. 2. If you do not know how to interpret a question, then ask me. 3. Questions 1- require

More information

Introduce the idea of a nondegenerate tableau and its analogy with nondenegerate vertices.

Introduce the idea of a nondegenerate tableau and its analogy with nondenegerate vertices. 2 JORDAN EXCHANGE REVIEW 1 Lecture Outline The following lecture covers Section 3.5 of the textbook [?] Review a labeled Jordan exchange with pivoting. Introduce the idea of a nondegenerate tableau and

More information

Introduction to linear programming using LEGO.

Introduction to linear programming using LEGO. Introduction to linear programming using LEGO. 1 The manufacturing problem. A manufacturer produces two pieces of furniture, tables and chairs. The production of the furniture requires the use of two different

More information

...(iii), x 2 Example 7: Geetha Perfume Company produces both perfumes and body spray from two flower extracts F 1. The following data is provided:

...(iii), x 2 Example 7: Geetha Perfume Company produces both perfumes and body spray from two flower extracts F 1. The following data is provided: The LP formulation is Linear Programming: Graphical Method Maximize, Z = 2x + 7x 2 Subject to constraints, 2x + x 2 200...(i) x 75...(ii) x 2 00...(iii) where x, x 2 ³ 0 Example 7: Geetha Perfume Company

More information

MS-E2140. Lecture 1. (course book chapters )

MS-E2140. Lecture 1. (course book chapters ) Linear Programming MS-E2140 Motivations and background Lecture 1 (course book chapters 1.1-1.4) Linear programming problems and examples Problem manipulations and standard form Graphical representation

More information

15-780: LinearProgramming

15-780: LinearProgramming 15-780: LinearProgramming J. Zico Kolter February 1-3, 2016 1 Outline Introduction Some linear algebra review Linear programming Simplex algorithm Duality and dual simplex 2 Outline Introduction Some linear

More information

Nonlinear Programming (Hillier, Lieberman Chapter 13) CHEM-E7155 Production Planning and Control

Nonlinear Programming (Hillier, Lieberman Chapter 13) CHEM-E7155 Production Planning and Control Nonlinear Programming (Hillier, Lieberman Chapter 13) CHEM-E7155 Production Planning and Control 19/4/2012 Lecture content Problem formulation and sample examples (ch 13.1) Theoretical background Graphical

More information

Economic Operation of Power Systems

Economic Operation of Power Systems Economic Operation of Power Systems Section I: Economic Operation Of Power System Economic Distribution of Loads between the Units of a Plant Generating Limits Economic Sharing of Loads between Different

More information

Section 12.4 Algebra of Matrices

Section 12.4 Algebra of Matrices 244 Section 2.4 Algebra of Matrices Before we can discuss Matrix Algebra, we need to have a clear idea what it means to say that two matrices are equal. Let's start a definition. Equal Matrices Two matrices

More information

SAMPLE QUESTIONS. b = (30, 20, 40, 10, 50) T, c = (650, 1000, 1350, 1600, 1900) T.

SAMPLE QUESTIONS. b = (30, 20, 40, 10, 50) T, c = (650, 1000, 1350, 1600, 1900) T. SAMPLE QUESTIONS. (a) We first set up some constant vectors for our constraints. Let b = (30, 0, 40, 0, 0) T, c = (60, 000, 30, 600, 900) T. Then we set up variables x ij, where i, j and i + j 6. By using

More information

Review Questions, Final Exam

Review Questions, Final Exam Review Questions, Final Exam A few general questions. What does the Representation Theorem say (in linear programming)? In words, the representation theorem says that any feasible point can be written

More information

CHAPTER 11 Integer Programming, Goal Programming, and Nonlinear Programming

CHAPTER 11 Integer Programming, Goal Programming, and Nonlinear Programming Integer Programming, Goal Programming, and Nonlinear Programming CHAPTER 11 253 CHAPTER 11 Integer Programming, Goal Programming, and Nonlinear Programming TRUE/FALSE 11.1 If conditions require that all

More information

LINEAR PROGRAMMING: A GEOMETRIC APPROACH. Copyright Cengage Learning. All rights reserved.

LINEAR PROGRAMMING: A GEOMETRIC APPROACH. Copyright Cengage Learning. All rights reserved. 3 LINEAR PROGRAMMING: A GEOMETRIC APPROACH Copyright Cengage Learning. All rights reserved. 3.4 Sensitivity Analysis Copyright Cengage Learning. All rights reserved. Sensitivity Analysis In this section,

More information

QUESTION ONE Let 7C = Total Cost MC = Marginal Cost AC = Average Cost

QUESTION ONE Let 7C = Total Cost MC = Marginal Cost AC = Average Cost ANSWER QUESTION ONE Let 7C = Total Cost MC = Marginal Cost AC = Average Cost Q = Number of units AC = 7C MC = Q d7c d7c 7C Q Derivation of average cost with respect to quantity is different from marginal

More information

Solution 1 Linear programming illustrating maximisation

Solution 1 Linear programming illustrating maximisation 20 Solutions Lindo software at www.lindo.com, and similar proprietary products, which facilitate interactive use from the keyboard or customised subroutines linked directly to form an integrated program,

More information

Linear Programming and the Simplex method

Linear Programming and the Simplex method Linear Programming and the Simplex method Harald Enzinger, Michael Rath Signal Processing and Speech Communication Laboratory Jan 9, 2012 Harald Enzinger, Michael Rath Jan 9, 2012 page 1/37 Outline Introduction

More information

Introduction to Lexicographic Reverse Search: lrs

Introduction to Lexicographic Reverse Search: lrs Introduction to Lexicographic Reverse Search: lrs June 29, 2012 Jayant Apte ASPITRG Outline Introduction Lexicographic Simplex Algorithm Lex-positive and Lex min bases The pitfalls in reverse search Lexicographic

More information

ISE 330 Introduction to Operations Research: Deterministic Models. What is Linear Programming? www-scf.usc.edu/~ise330/2007. August 29, 2007 Lecture 2

ISE 330 Introduction to Operations Research: Deterministic Models. What is Linear Programming? www-scf.usc.edu/~ise330/2007. August 29, 2007 Lecture 2 ISE 330 Introduction to Operations Research: Deterministic Models www-scf.usc.edu/~ise330/007 August 9, 007 Lecture What is Linear Programming? Linear Programming provides methods for allocating limited

More information

Unit 3. Linear Programming. The simplex method

Unit 3. Linear Programming. The simplex method Unit 3. Linear Programming. The simplex method Operations Research is a branch of Mathematics which generally relates to problems when the aim is to find a method for finding the best solution to a problem

More information