5. INTRODUCTION TO LINEAR PROGRAMMING (LP) Learning Objectives 1. Obtain an overview of the kinds of problems linear programming has been used to solve. 2. Learn how to develop linear programming models for simple problems. 3. Be able to identify the special features of a model that make it a linear programming model. 4. Learn how to solve two variable linear programming models by the graphical solution procedure. 5. Understand the importance of extreme points in
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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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INTRODUCTION My topic is oil refinering using linear programming‚ this is under petrochemical industries which mean it will deal more about chemicals‚ this is about optimising the cost using a modelling method in mathematics called linear programming. This is very important because it links what is done in petrochemical industries with mathematics. Since there is a huge need of the products that are produced after petroleum refinering which are petrol‚ gasoline‚ oil‚ diesel and etc so in the
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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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|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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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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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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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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