Anything that can be done to reduce lead-time will improve forecast accuracy. * Bias indicates the directional tendency of FE <------> MAD indicates the magnitude of FE (Weighted) Moving Averages The Exponential Smoothing Method; Linear Combination * Another special case of Weighted Moving Average * F t = F t-1 + α (X t-1 - F t-1 ) II. Aggregate Production Planning Production Planning strategies: Level‚ Chase‚ and Combination * Level:
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limitations. Quantitative approach to decision making‚ models & modeling in Operations Research. Module II (8 Hours) Linear programming‚ Structure of linear program model‚ Assumption‚ Advantages‚ Limitations‚ General mathematical model‚ Guidelines for formulation of linear programming model‚ Graphical method‚ algorithm (Only illustrative problems) Duality in linear programming.. Module III (8 Hours) Transportation problem‚ General structure of transportation problem‚ methods of finding initial
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computers in this field. [5 Marks] 2. Explain how the linear programming technique can be helpful in decision-making in the areas of Marketing and Finance. [10 Marks] 3. a. How do you recognise optimality in the simplex method? b. Write the role of pivot element in simplex table? [5 Marks] [5 Marks] 4. What is the significance of duality theory of linear programming? Describe the general rules for writing the dual of a linear programming problem. [10 Marks] 5. Use Two-Phase simplex method
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16 25 29 24 When the metals are processed and refined‚ the impurities are removed. The company wants to know the amount of each ore to use per ton of the alloy that will minimize the cost per ton of the alloy. a. Formulate a linear programming model for this problem. b. Solve the model by using the computer. 19. As a result of a recently passed bill‚ a congressman’s district has been allocated $4 million for programs and projects. It is up to the congressman to decide
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within 2 hours of opening it - Content: - General knowledge on the background of operations research/management science - Value of operations research/management science - Modeling basics (types‚ applications‚ etc.) - Linear programming/Integer Linear Programming basics (difference between the two‚ building an LP/ILP model‚ integration of the model into Excel‚ optimal solution‚ feasible region‚ establishing constraints‚ bounded/unbounded solutions‚ sensitivity analysis) - Network Modeling
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decision time Decision making is an important aspect of the Paper F5 syllabus‚ and questions on this topic will be common. The range of possible questions is considerable‚ but this article will focus on only one: linear programming. The ideas presented in this article are based on a simple example. Suppose a profit-seeking firm has two constraints: labour‚ limited to 16‚000 hours‚ and materials‚ limited to 15‚000kg. The firm manufactures and sells two products‚ X and Y. To make X‚ the firm uses 3kg of
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following table gives the time‚ in minutes‚ to perform the tasks at each assembly point for the individual teams. Assembly 2 26 24 26 24 26 Point 3 40 30 28 36 30 4 30 32 36 30 40 5 26 18 18 20 24 Team A B C D E 1 20 22 24 20 20 Formulate a linear programming model that will minimize the total assembly time for a printer. 6. Why is implementation a difficult aspect of the quantitative modeling process? Caston Sigauke 2006 1 7. A post office requires different numbers of full-time employees on
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whereas each bracelet requires 2 ounces of gold and 5 ounces of platinum. The store has to use a minimum of two ounces of gold. The demand for bracelet is no less than three. A necklace earns $375 in profit and a bracelet‚ $225. Formulate a linear programming model for this problem with an appropriate objective function =number of necklaces to be made = number of bracelets to be made Maximize Profit (Z)= Subject to Maximum availability of gold Minimum usage quantity of gold Maximum availability
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------------------------------------------------------------------------------------------------------------ Week 1 Introduction Ch.1 Module 1 ------------------------------------------------------------------------------------------------------------ Week 2 Linear Programming Ch. 2 Module 2 HW#1 (LP) ------------------------------------------------------------------------------------------------------------ Week 3 LP: Sensitivity Ch. 3 Module 3 HW#2 Analysis and Computer Solution ------------
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Introduction to Optimization Course Notes for CO 250/CM 340 Fall 2012 c Department of Combinatorics and Optimization University of Waterloo August 27‚ 2012 2 Contents 1 Introduction 1.1 An example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 1.1.2 1.2 1.3 1.2.1 1.3.1 1.3.2 1.4 1.4.1 1.4.2 1.5 1.5.1 1.5.2 1.6 1.6.1 1.6.2 1.6.3 1.7 1.8 2 The formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . Correctness . . . . . . . . . . . . . . . .
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