The third edition of this highly-regarded text has been fully updated whilst maintaining the accessible and comprehensive style that makes this text so popular.Packed with diverse realistic examples from Scotland to Saudi Arabia, this truly internationalized version of the landmark text from the Anderson, Sweeney and Williams team provides a complete introduction to the subjects of Management Science and Operations Research.
The third edition of this highly-regarded text has been fully updated whilst maintaining the accessible and comprehensive style that makes this text so popular.Packed with diverse realistic examples from Scotland to Saudi Arabia, this truly internationalized version of the landmark text from the Anderson, Sweeney and Williams team provides a complete introduction to the subjects of Management Science and Operations Research.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
David R. Anderson is Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He earned his BS, MS and PhD degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration at the University of Cincinnati. In addition, he was the coordinator of the College's first Executive Program. At the University of Cincinnati, Professor Anderson has taught introductory statistics for business students as well as graduate-level courses in regression analysis, multivariate analysis and management science. He has also taught statistical courses at the Department of Labor in Washington, D.C. He has been honoured with nominations and awards for excellence in teaching and excellence in service to student organizations. Professor Anderson has co-authored 10 textbooks in the areas of statistics, managemen
t science, linear programming and production and operations management. He is an active consultant in the field of sampling and statistical methods.
Dennis J. Sweeney is Professor of Quantitative Analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. He has published more than 30 articles in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences and other journals. Professor Sweeney has co-authored ten textbooks in the areas of statistics, management science, linear programming and production and operations management.
Inhaltsangabe
1.Introduction2.An Introduction to Linear Programming3.Linear Programming: Sensitivity Analysis and Interpretation of Solution4.Linear Programming Applications5.Linear Programming: The Simplex Method6.Simplex-Based Sensitivity Analysis and Duality7.Transportation, Assignment and Transshipment Problems8.Network Models9.Project Scheduling: PERT/CPM10.Inventory Models11.Queuing Models12.Simulation13.Decision Analysis14.Multicriteria DecisionsConclusion: Management Science in PracticeAppendix A Areas for the Standard Normal DistributionAppendix B Values of e_lAppendix C Bibliography and ReferencesAppendix D Self-Test SolutionsOnline chapters15.Integer Linear Programming16.Forecasting17.Dynamic Programming18.Markov Processes
1.Introduction2.An Introduction to Linear Programming3.Linear Programming: Sensitivity Analysis and Interpretation of Solution4.Linear Programming Applications5.Linear Programming: The Simplex Method6.Simplex-Based Sensitivity Analysis and Duality7.Transportation, Assignment and Transshipment Problems8.Network Models9.Project Scheduling: PERT/CPM10.Inventory Models11.Queuing Models12.Simulation13.Decision Analysis14.Multicriteria DecisionsConclusion: Management Science in PracticeAppendix A Areas for the Standard Normal DistributionAppendix B Values of e_lAppendix C Bibliography and ReferencesAppendix D Self-Test SolutionsOnline chapters15.Integer Linear Programming16.Forecasting17.Dynamic Programming18.Markov Processes
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