(a) What is linear programming problem? Ans: Linear programming (LP‚ or linear optimization) is a mathematical method for determining a way to achieve the best outcome (such as maximum profit or lowest cost) in a given mathematical model for some list of requirements represented as linear relationships. Linear programming is a specific case of mathematical programming (mathematical optimization). More formally‚ linear programming is a technique for the optimization of a linear objective function
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Chapter 12 Data Envelopment Analysis Data Envelopment Analysis DEA is an increasingly popular management tool. This write-up is an introduction to Data Envelopment Analysis DEA for people unfamiliar with the technique. For a more in-depth discussion of DEA‚ the interested reader is referred to Seiford and Thrall 1990 or the seminal work by Charnes‚ Cooper‚ and Rhodes 1978 . DEA is commonly used to evaluate the e ciency of a number of producers. A typical statistical approach is characterized
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Introduction to Linear Programming Linear Programming: Sensitivity Analysis and Interpretation of Solution Linear Programming Applications in Marketing‚ Finance and Operations Management Advanced Linear Programming Applications Distribution and Network Models Integer Linear Programming Nonlinear Optimization Models Project Scheduling: PERT/CPM Inventory Models Waiting Line Models Simulation Decision Analysis Multicriteria Decisions Forecasting Markov Processes Linear Programming: Simplex Method Simplex-Based
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|Lovely Professional University‚ Punjab | | | | | | |
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performance of the system. Techniques and tools of operation research: Linear programming: You can use linear programming to find a solution for optimising a given objective. The objective may be to maximize profit or to minimize cost. Inventory control methods: The production‚ purchasing‚ and material managers are always confronted with questions‚ such as when To buy‚ and how much to keep in stock. Goal programming: In linear programming ‚ you take a single objective function and consider all other factors
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Simulation with ARENA Khalil Management of Technology Kolarik Creating Quality: Concepts‚ Systems‚ Strategies‚ and Tools Creating Quality: Process Design for Results Law and Kelton Simulation Modeling and Analysis Nash and Sofer Linear and Nonlinear Programming Nelson Stochastic Modeling: Analysis and Simulation Niebel and Freivalds Methods‚
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Research. Briefly explain the techniques and tools of Operations Research. Operations Research Methodology 10 Techniques and tools of Operations Research 2 Explain the steps involved in linear programming problem formulation with an example. Discuss in brief the advantages of linear programming. Q1 : Discuss the various stages involved in the methodology of Operations Research. Briefly explain the techniques and tools of Operations Research. 1. Operations Research Methodology 2. Techniques
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13 16 14 6 20 100 MARKS RECEIVED 1 Question 1 Graphical solution (16 marks) For a linear programming model given below: Decision variables x1 Units of product 1 to produce. x2 – Units of product 2 to produce. Objective function Maximize 4.0x1 + 3.6x2 Constraints Constraint 1: 11x1 + 5x2 > 55 Constraint 2: 3x1 + 4x2 < 36 Constraint 3: 4x1 – 9x2 < 0 Nonnegativity: x1‚ x2 >= 0 Solve this linear programming model by using the graphical approach (Graph paper is provided on the next page). For your
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is a tool to model and solve linear and nonlinear programming problems. To access it‚ open Excel‚ choose the tab “Data” and select “Solver” from the “Analysis” group. If it is not there‚ you have to install it‚ by clicking the “File” tab (or the Office button)‚ then “Options”‚ then “Add-Ins”‚ and then “Manage Add-Ins”. Check “Solver” there. To solve the model‚ you have to first program in on a spreadsheet. In the attached “excel-example.xls” we solve the linear programming problem max 3x1 + 2x2 s.t. 2x1
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giving step-wise information about the methodology and solution. TORA tutorial software deals with the following algorithms: •Solution of simultaneous linear equations •Linear programming •Transportation model •Integer programming •Network models •Project analysis by CPM/PERT •Poisson queuing models •Zero-sum games The software provides a number
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