Description
McGraw Hill Introduction to Operations Research 2021 Edition by Gerald J. Lieberman, Frederick S. Hillier, Bodhibrata Nag, Preetam Basu
For over four decades, Introduction to Operations Research has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the art, user-friendly software and more coverage of business applications than ever before. The hallmark features of this edition include new section and chapters, updated problems, clear and comprehensive coverage of fundamentals, an extensive set of interesting problems and Indian cases, and state-of-the-practice operations research software used in conjunction with examples from the text.Key Features• Four new sections describe analytics as a key new complement to operations research• A new section provides an elementary introduction to one of the most widely used techniques of operations research, that is, the theory of simulation optimization.• A new section describes how decision analysis now is being widely extended to multiple criteria decision analysis to understand how multiple criteria can be considered in operations research studies• India-centric case studies on applications of linear and integer programming, revenue management techniques, transportation problem, traveling salesman problem, vehicle routing problem, facility location, genetic algorithms, simulation, decision analysis and inventory management• Coverage of Revenue Optimization, Analytic Hierarchy Process, Multi-objective Decision Making techniques, Data Envelopment Analysis, AMPL and R software for optimization and AnyLogic simulation software• Vignettes covering real life and industrial applications of various operations research tools and techniques. Table of Contents : - 1) Introduction2) Overview of How Operations Research and Analytics Professionals Analyze Problems3) Introduction to Linear Programming4) Solving Linear Programming Problems: The Simplex Method5) The Theory of the Simplex Method6) Duality Theory7) Linear Programming under Uncertainty (Available Online)8) Other Algorithms for Linear Programming (Available Online)9) The Transportation and Assignment Problems10) Network Optimization Models11) Dynamic Programming12) Integer Programming13) Nonlinear Programming14) Metaheuristics15) Game Theory16) Decision Analysis17) Queueing Theory18) Inventory Theory (Available Online)19) Markov Decision Processes20) Simulation21) The Art of Modeling with Spreadsheet (Available Online)22) Project Management with PERT/CPM (Available Online)23) Additional Special Types of Linear Programming Problems (Available Online)24) Probability Theory (Available Online)25) Reliability (Available Online)26) The Application of Queueing Theory (Available Online)27) Forecasting (Available Online)28) Markov Chains (Available Online)Appendix 1 - Documentation for the OR Courseware (Available Online)Appendix 2 – Convexity (Available Online)Appendix 3 - Classical Optimization Methods (Available Online)Appendix 4 - Matrices and Matrix Operations (Available Online)Appendix 5 - Table for a Normal Distribution (Available Online)Partial Answers to Selected Problems (Available Online)Author IndexSubject Index.