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    constrain). x2 ≤ 500 (Dress constrain). And the non-negative constrains are x1 ≥0‚ x2 ≥0 Maximize the profit function: p = 3x1 + 5x2 2. What are the advantages of Linear programming techniques? Ans. Advantages— 1. The linear programming technique helps to make the best possible use of available productive resources (such as time‚ labour‚ machines etc.) 2. It improves the quality of decisions. The individual who makes use of linear programming methods becomes more objective than

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    (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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    describe the line of business (product types etc.)‚ noting the type of environment (MTS‚ ATO or MTO). Coca-Cola is an American multinational beverage corporation that was found on 1892 by Asa Candler and is a manufacturer‚ retailer and marketer of non-alcoholic beverage concentrates and syrups. Coca-Cola operate in a make- to -stock enviroment. This process can help to provide faster service to customers from available stock and lower costs considering Coke normally has a distribution process of

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    NAME: TIME: 3 hours (180 minutes) PAGES: 20 (including this cover page) INSTRUCTIONS: 1. Total Mark Value: 100 Number of questions: 7 2. 1 page (single-sided-letter-sized) notes are permitted. 3. Stand-alone-non-programmable calculators are permitted. 4. Budget your time carefully. 5. Answers are to be given in the space provided. However‚ should you require additional space for a complete answer‚ use the blank page attached for this purpose. 6. For all problems where calculation space is

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    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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    analysis before attempting to use structural modeling. Major applications of structural equation modeling include: 1. causal modeling‚ or path analysis‚ which hypothesizes causal relationships among variables and tests the causal models with a linear equation system. Causal models can involve either manifest variables‚ latent variables‚ or both; 2. confirmatory factor analysis‚ an extension of factor analysis in which specific hypotheses about the structure of the factor loadings and intercorrelations

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    IEOR 4000: Production Management Lecture 5 1 Professor Guillermo Gallego 9 October 2001 Aggregate Production Planning Aggregate production planning is concerned with the determination of production‚ inventory‚ and work force levels to meet fluctuating demand requirements over a planning horizon that ranges from six months to one year. Typically the planning horizon incorporate the next seasonal peak in demand. The planning horizon is often divided into periods. For example‚ a one

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    represent linear transformations‚ that is‚ generalizations of linear functions such as f(x) = 4x. For example‚ the rotation of vectors in three dimensional space is a linear transformation. If R is a rotation matrix and v is a column vector (a matrix with only one column) describing the position of a point in space‚ the product Rv is a column vector describing the position of that point after a rotation. The product of two matrices is a matrix that represents the composition of two linear transformations

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    1 80 5.2 a. Construct a scatter diagram showing the hours against the unit numbers. Is the relationship between hours and unit numbers linear or non-linear? b. Construct a scatter diagram showing the ln(hours) against the ln(unit numbers). Comment on whether the relationship between ln(hours) and ln(unit numbers) is linear or non-linear. c. Using the linear regression method to derive the learning curve function (Please show your work by using the formulas in Lesson 02). What is the rate of learning

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