Lecture 1

Lecture 1 - 540:311 DETERMINISTIC MODELS IN OPERATIONS...

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540:311 DETERMINISTIC MODELS IN OPERATIONS RESEARCH Lecture 1: Introduction, Administration, Examples of mathematical programs Class Meeting: MTH 2 10:20-11:40am (SEC-209) Recitation W6-7pm (SEC-217) Prof. W. Art Chaovalitwongse (Dr. Chao-va-lit-wongs, Dr. Art, Dr. C, etc)
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General Information Instructor: W. Art Chaovalitwongse Office: CoRE Building, Rm. 212 E-mail: [email protected] Phone: 732-445-5469 Office Hours: M,W 1.30-3.00 pm TA: Chun-An (Joe) Chou E-mail: [email protected] Prerequisite – Matrix and Numerical Methods, basic knowledge of operations research, linear algebra, and basic calculus Software – Lindo (comes with text book) – Excel – AMPL/CPLEX or GAMS/CPLEX
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Text Books W. Winston. Operations Research: Applications and Algorithms 4th edition, Brooks/Cole, 2003 Hardcover: 1440 pages Publisher: Duxbury Press; 4 edition (July 25, 2003) Language: English ISBN-10: 0534380581 ISBN-13: 978-0534380588 (same book used in Prob Models in OR)
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Course Logistics Homeworks: 10% – (lowest homework score will be dropped) Quizzes: 10% – (lowest quiz score will be dropped) Project: 10% (a group of 3-4 students) Midterm 1: 20% Midterm 2: 20% Final: 30%
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1.1 An Introduction to Modeling Operations research (management science) is a scientific approach to decision making that seeks to best design and operate a system, usually under conditions requiring the allocation of scarce resources. – Term coined during WW II when leaders asked scientists and engineers to analyze several military problems. A system is an organization of interdependent components that work together to accomplish the goal of the system. The scientific approach to decision making requires the use of one or more mathematical models . A mathematical model is a mathematical representation of the actual situation that may be used to make better decisions or clarify the situation.
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Mathematical Modeling Prescriptive models “prescribe” behavior for an organization that will enable it to best meet its goals. – Components of this model include: • objective function(s) • decision variables • constraints An optimization model seeks to find values of the decision variables that optimize (maximize or minimize) an objective function among the set of all values for the decision variables that satisfy the given constraints.
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Decision variables: – the quantities that can vary; we often call them simply variables Objective function: – the expression that is being minimized or maximized Constraints: – equations and inequalities that the decision variables must satisfy Solution: – an assignment of values to the decision variables Feasible solution: – an assignment of values to the variables that satisfies all of its constraints. Optimal solution:
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This note was uploaded on 09/20/2011 for the course ENG 300 taught by Professor Albin during the Fall '11 term at Rutgers.

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Lecture 1 - 540:311 DETERMINISTIC MODELS IN OPERATIONS...

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