An Introductory Approach to Operations Research

An Introductory Approach to Operations Research

An Introductory Approach to Operations Research

An Introductory Approach to Operations Research

Excerpt

Although this book owes much of its content to the highly successful Decision Making Through Operations Research, 2nd Edition, by Robert J. Thierauf and Robert C. Klekamp ( Wiley/ Hamilton, 1975), it possesses its own character and has been written to satisfy a particular need of those who teach the introductory course in Operations Research. Chiefly, it presents the basic techniques of operations research (OR) as well as the important requirements for formulating specifical OR models, resulting in a "model formulation" approach to an introductory study of operations research.The level of presentation is geared toward the undergraduate business student. Within this framework, the book contains features that assist the student in learning about operations research as practiced within a typical business organization. These student-oriented learning activities are found in each chapter:

• study goals for the chapter, accompanied by a chapter outline

• the requirements for formulating operations research models to solve specific

• business problems applications of OR models to specific business problem areas

• summaries of operations research methodology or steps that are involved in a specific OR model

• questions, model formulation exercises, and mathematical exercises at the end of each chapter, with answers to the latter (Appendix E)

• These pedagogical tools also assist the instructor whose time may be somewhat limited, because of large classes.

The structure of the book follows a logical sequence for presenting a comprehensive treatment of standard OR techniques. Part I, focuses on an overview of operations research and model formulation; Part II presents traditional business models; namely, breakeven and inventory, that rely on algebra for their solution. Decision theory, decision models treating a variable demand, and PERT (Program Evaluation and Review Technique) models that utilize probability and statistics are set forth in Part III. In Part IV, the underlying mathematics of matrix algebra is employed for linear programming, transportation methods, dynamic programming, and Markov analysis. Due to the importance of simulation techniques, queuing and simulation models are presented in Part V. Lastly, advanced operations research topics and an overview of the present and future directions of OR make up Part VI. In addition, background on vectors, matrices . . .

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