application of logical and quantitative analysis to business decision making and problem solving. It familiarizes the student with a wide range of software and other classical and contemporary resources related to decision and problem analysis, including basics of logic and decision making, principles of optimization, probabilistic distributions, linear programming, simplex, queuing and transportation problems, break even analysis, inventory management, forecasting and simulation. The course
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1 0.1.1 Linear Programming Objectives By the end of this unit you will be able to: • formulate simple linear programming problems in terms of an objective function to be maximized or minimized subject to a set of constraints. • find feasible solutions for maximization and minimization linear programming problems using the graphical method of solution. • solve maximization linear programming problems using the simplex method. • construct the Dual of a linear programming problem. • solve minimization
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Shanti Business School PGDM Batch 2015-17 Semester II Course Outline 1 Shanti Business School, Ahmedabad PGDM 2015-17: Program Structure Semester-1 Semester-2 Semester-3 Semester-4 Course credit Course credit Course credit Language Skills @ Written Analysis & Communication @ Soft skills II @ Employability Skills @ IT & MIS 2 Soft skills I @ Computing skills 2 Social Media Marketing @ 2 Legal Aspects
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Linear Programming: Using Solver in Excel Linear Programming was conceptually developed before World War II by the outstanding Russian mathematician A.N.Kolmogorov and gained its popularity ever since the development of Simplex method by George B. Dantzig in 1947. Linear programming deals with problems of maximizing or minimizing a linear function in the presence of linear equality and/or inequality constraints. In these problems, we find the optimal, or most efficient way of using limited resources
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BASIC LINEAR PROGRAMMING 18.0 LEARNING OBJECTIVES After studying this chapter, readers should be able to: Understand the concept and meaning of linear programming; Know the underlying basic assumptions; Formulate the linear programming problem; Solve linear programming problem using graphical and Simplex methods; and make appropriate and correct interpretations; and Understand the concepts of duality and shadow cost in linear programming. 18.1 INTRODUCTION This is an Operations Research
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LINEAR PROGRAMMING II 1 Linear Programming II: Minimization © 2006 Samuel L. Baker Assignment 11 is on page 16. Introduction A minimization problem minimizes the value of the objective function rather than maximizing it. Minimization problems generally involve finding the least-cost way to meet a set of requirements. Classic example -- feeding farm animals. Animals need: 14 units of nutrient A, 12 units of nutrient B, and 18 units of nutrient C. Learning Objective 1: Recognize problems that
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course you are expected to • Formulate real world decision making situations as mathematical optimisation problems • Solve linear programming problems • Be able to understand what the solution means • Understand basic concepts of transportation, assignment and integer programming problems. Reference [1] F.S.Hillier and M.S.Hillier, Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets, Tata McGraw-Hill, New Delhi,. [2] H.A.Taha, Operations Research
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Optimizing Printed Circuit Board Production: A Case Study Abstract This paper focuses on the production of 5 different printed circuit boards (PCBs). The purpose of this paper is to understand the best production model to reach maximum profit. It is understood that there are production capacities that will limit the overall amount of products produce. Through the use of Linear Programming we can determine, based on the current circuit boards sale price, the number of each board type the plant
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Solutions to Case Problems Manual to Accompany An Introduction To Management Science Quantitative Approaches To Decision Making Twelfth Edition David R. Anderson University of Cincinnati Dennis J. Sweeney University of Cincinnati Thomas A. Williams Rochester Institute of Technology R. Kipp Martin University of Chicago South-Western Cincinnati, Ohio Contents Preface Chapter 1: Introduction ♦ Scheduling a Golf League Chapter 2: An Introduction to Linear Programming ♦ Workload
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Supplement 1 Linear Programming with Transportation in Operations Management LEARNING OBJECTIVES After studying this technical supplement, you should be able to: 1. Explain the importance of optimization to operations management 2. Demonstrate how to develop linear programming models 3. Show how linear programming models can be solved using EXCEL 4. Demonstrate 0-1, transportation, and assignment models LINEAR PROGRAMMING MODELS IN OPERATIONS MANAGEMENT Linear programming (LP)
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