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    Chapter 2 An Introduction to Linear Programming 18. a. Max 4A + 1B + 0S1 + 0S2 + 0S3 s.t. 10A + 2B + 1S1 = 30 3A + 2B + 1S2 = 12 2A + 2B + 1S3 = 10 A‚ B‚ S1‚ S2‚ S3  0 b. c. S1 = 0‚ S2 = 0‚ S3 = 4/7 23. a. Let E = number of units of the EZ-Rider produced L = number of units of the Lady-Sport produced Max 2400E + 1800L s.t. 6E + 3L  2100 Engine time L  280 Lady-Sport maximum

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    Quantitative Methods in Business – Linear Programming 1- Statement of the Problem: Middle East for investment offers a bundle of investment options in many types of securities. Mr. Brown‚ an investor‚ would like to invest $ 5 million in various securities. He wishes to maximize his yearly profit over the next year. The investment company offered him a portfolio including Bonds‚ Stocks‚ Gold and Land. The expected return is 6% for Bonds‚ 14% for Stocks‚ 10% for Gold and 5% for Land. For diversification

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    17th International Mining Congress and Exhibition of Turkey- IMCET 2001‚ © 2001‚ ISBN 975-395-417-4 Optimum Blending of Coal by Linear Programming for the Power Plant at Seyitömer Coal Mine K.Erarslan‚ H.Aykul‚ H.Akçakoca & N.Çetin Dumlupınar University‚ Department of Mining Engineering‚ 43100‚ Kütahya‚ Turkey ABSTRACT: In this study‚ a linear programming model is developed to determine the optimum coal blend in terms of quality and quantity. Coal with various features is mined from different

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    Linear Programming Model in Operation Research study is usually mathematical type of model which contains set of equations that represent objective function and constraints. The keywords in this article are Objective Function and Constraints‚ according to Heizer & Render (2008) Objective Function are mathematical expression expressed in linear programming designed to maximizes or minimizes some quantity‚ for example profit can maximized while the cost might be reduced. The objective function is also

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    Manufacturing Industries Using Linear Programming Techniques: Geepee Nigeria Limited Fagoyinbo‚ I. S. * Akinbo‚ R. Y. * Ajibode‚ I. A.* * Department of Mathematics and Statistics‚ Federal Polytechnic‚ Ilaro‚Ogun State‚ Nigeria ** Olaniran‚ Y.O.A ** Department of Marketing‚Federal Polytechnic‚ Ilaro‚Ogun State‚ Nigeria Abstract Any organization set up aims at maximization of profit from its investment from minimum cost of objective function. This research work applies the concept

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    Programme: BTEC Higher National Diploma (HND) in Computing H2 Unit Number and Title: Unit 41: Programming in Java Assignment Ref. Number: 41.1- Sample programming using JAVA applications. Module Tutor: Murshed Thakur Email: murshed.edu@gmail.com/g.murshed@theiet.org Date Set: Learner’s Name: …… …………………………. Learner’s ID: ………………………………… Date handed-in: ….:……………… Plagiarism Statement I declare that‚ apart from properly referenced quotations‚ this report is my own work and

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    Reviewer for MANSCIE 1. Introduction to Quantitative Analysis Approach Quantitative Analysis involves the use of mathematical equations or relationships in analyzing a particular problem. Steps in Quantitative Analysis Approach 1. Define the problem 2. Develop a model 3. Acquire input data 4. Develop a solution 5. Test the solution 6. Analyze the results 7. Implement the results 2. Decision Theory Six steps in decision making 1. Define the problem 2. List possible alternatives 3. Identify possible

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    (Balakrishnan/Render/Stair) Chapter 2 Linear Programming Models: Graphical and Computer Methods 2.1 Chapter Questions 1) Consider the following linear programming model: Max X12 + X2 + 3X3 Subject to: X1 + X2 ≤ 3 X1 + X2 ≤ 1 X1‚ X2 ≥ 0 This problem violates which of the following assumptions? A) certainty B) proportionality C) divisibility D) linearity E) integrality Answer: D Page Ref: 22 Topic: Developing a Linear Programming Model Difficulty: Easy 2) Consider the following linear programming model: Min 2X1

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    Linear Programming is a mathematical technique useful for allocation of scarce or limited resources to several competing activities on the basis of given criterion of optimality.The usefulness of linear programming as a tool for optimal decision-making on resource allocation‚ is based on its applicability to many diversified decision problems. The effective use and application requires‚ as on its applicability to many diversified decision problems. The effective use and application requires‚ as a

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    Operational Research (OR) DR. SUPRIYA KUMAR DE ASSIGNMENT XLRI-PGCBM-18 NAME: GH. RASOOL WANI SMS ID: 2217429 Table of Contents 1. Problem: 1 2. Solution: 2 2.1 Manual Approach 2 2.2 Linear programming approach 2 2.2.1 Decision Variables: 3 2.2.2 Objective Function: 3 2.2.3 Constraints: 3 2.3 Excel Solution. 6 2.3.1 Excel Solution Embedded: 6 3. Analysis: 6 3.1 Sensitivity Analysis: Objective Function 6 3.2 Sensitivity Analysis:

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