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    The development of linear programming has been ranked among the most important scientific advances of the mid 20th century. Its impact since the 1950’s has been extraordinary. Today it is a standard tool used by some companies (around 56%) of even moderate size. Linear programming uses a mathematical model to describe the problem of concern. Linear programming involves the planning of activities to obtain an optimal result‚ i.e.‚ a result that reaches the specified goal best (according to the mathematical

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    Chapter 8 Linear Programming Applications To accompany Quantitative Analysis for Management‚ Eleventh Edition‚ Global Edition by Render‚ Stair‚ and Hanna Power Point slides created by Brian Peterson Copyright © 2012 Pearson Education 8-1 Learning Objectives After completing this chapter‚ students will be able to: 1. Model a wide variety of medium to large LP problems. 2. Understand major application areas‚ including marketing‚ production‚ labor scheduling‚ fuel blending‚ transportation‚ and

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    PAPER ON LINEAR PROGRAMMING Vikas Vasam ID: 100-11-5919 Faculty: Prof. Dr Goran Trajkovski CMP 561: Algorithm Analysis VIRGINIA INTERNATIONAL UNIVERSITY Introduction: One of the section of mathematical programming is linear programming. Methods and linear programming models are widely used in the optimization of processes in all sectors of the economy: the development of the production program of the company‚ its distribution

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    An Introduction to Linear Programming Steven J. Miller∗ March 31‚ 2007 Mathematics Department Brown University 151 Thayer Street Providence‚ RI 02912 Abstract We describe Linear Programming‚ an important generalization of Linear Algebra. Linear Programming is used to successfully model numerous real world situations‚ ranging from scheduling airline routes to shipping oil from refineries to cities to finding inexpensive diets capable of meeting the minimum daily requirements. In many of these problems

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    TOPIC – LINEAR PROGRAMMING Linear Programming is a mathematical procedure for determining optimal allocation of scarce resources.   Requirements of Linear Programming •        all problems seek to maximize or minimize some quantity •        The presence of restrictions or constraints •        There must be alternative courses of action •        The objective and constraints in linear programming must be expressed in terms of linear equations or inequalities   Objective

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    PROBLEM NUMBER 1 A farmer can plant up to 8 acres of land with wheat and barley. He can earn $5‚000 for every acre he plants with wheat and $3‚000 for every acre he plants with barley. His use of a necessary pesticide is limited by federal regulations to 10 gallons for his entire 8 acres. Wheat requires 2 gallons of pesticide for every acre planted and barley requires just 1 gallon per acre. What is the maximum profit he can make? SOLUTION TO PROBLEM NUMBER 1 let x = the number of acres of wheat

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    available in the tables attached with the question paper. Question 1 (15 points) Software effort estimation‚ measured in number of hours required to develop software‚ is an important activity associated with any software development company. It is used for investment planning and pricing of the software development. One approach usually used for software effort estimation is through Function Point Analysis (FPA). First made public by Allan Albrecht of IBM in 1979‚ the FPA technique

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    Z00_REND1011_11_SE_MOD7 PP2.QXD 2/21/11 12:39 PM Page 1 7 MODULE Linear Programming: The Simplex Method LEARNING OBJECTIVES After completing this chapter‚ students will be able to: 1. Convert LP constraints to equalities with slack‚ surplus‚ and artificial variables. 2. Set up and solve LP problems with simplex tableaus. 3. Interpret the meaning of every number in a simplex tableau. 4. Recognize special cases such as infeasibility‚ unboundedness and degeneracy. 5

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    spreadsheet‚ next step is to use the Solver to find the solution. In the Solver‚ we need to identify the locations (cells) of objective function‚ decision variables‚ nature of the objective function (maximize/minimize) and constraints. Example One (Linear model): Investment Problem Our first example illustrates how to allocate money to different bonds to maximize the total return (Ragsdale 2011‚ p. 121). A trust office at the Blacksburg National Bank needs to determine how to invest $100‚000 in following

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    from another mill. Fabrics that cannot be woven at the Southern Mill because of limited loom capacity will be purchased from another mill. The purchase price of each fabric is also shown in Table 1. MANAGERIAL REPORT I. - Develop a Linear Programming Model that can be used to schedule production for the Southern Textile Mill‚ and at the same time to determine how many yards of each fabric must be purchased from another mill. The model should be clear and complete.

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