An introduction to management science : quantitative approaches to decision making / 10th ed.

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作   者:David R. Anderson, Dennis J. Sweeney, Thomas A. Williams.

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ISBN:9780324145632

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简介

Summary: Publisher Summary 1 Upgrades to this edition include extended coverage of decision analysis and linear programming applications of revenue management systems and conjoint analysis. The 18 chapters include a glossary, new case problems and "management science in practice" vignettes, and self-tests; some chapters additionally offer material on using spreadsheets for forecasting. Appendices include statistical tables and an answer key to selected problems. Ancillary teaching and learning guides are available. Jumping the gun by most of a year, this volume carries a copyright date of 2003; dates are not given for previous iterations, except for a note indicating that the original edition appeared some 20 years ago. Anderson is at the U. of Cincinnati. Annotation c. Book News, Inc., Portland, OR (booknews.com)   Publisher Summary 2 ASW's Introduction to Management Science: A Quantitative Approach to Decision Making, 10e provides thorough, application-oriented coverage in a very readable writing style. This is the best traditional text on the market. Simply put, this is a classic! The problem-scenario approach introduces quantitative procedures through situations that include both problem formulation and technique application.The extensive linear programming coverage includes problem formulation, computer solution, and practical application. The text covers transportation, assignment, and the integer programming extension of linear programming, as well as advanced topics like waiting line models, simulation, and decision analysis. A large selection of problems includes self-test problems with complete solutions and case problems. Excel spreadsheet appendices are included in this edition as well.  

目录

Preface
About the Authors
Introduction p. 1
An Introduction to Linear Programming p. 31
Linear Programming: Sensitivity Analysis and Interpretation of Solution p. 90
Linear Programming Applications p. 147
Linear Programming: The Simplex Method p. 224
Simplex-Based Sensitivity Analysis and Duality p. 267
Transportation, Assignment, and Transshipment Problems p. 296
Integer Linear Programming p. 368
Network Models p. 412
Project Scheduling: PERT/CPM p. 442
Inventory Models p. 479
Waiting Line Models p. 525
Simulation p. 565
Decision Analysis p. 624
Multicriteria Decision Problems p. 687
Forecasting p. 731
Markov Processes p. 781
Dynamic Programming p. 806
Areas for the Standard Normal Distribution p. 835
Values of e[superscript -[lambda]] p. 836
References and Bibliography p. 837
Answers to Even-Numbered Problems p. 839
Solutions to Self-Test Problems p. 851
Index p. 874

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