Operations Research : An Introduction 8th Edition

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This eighth edition of Operations Research continues to build on the strengths of the first seven editions, providing balanced coverage of the theory, applications, and computations of operations research. This isa major revision, one that streamlines the presentation of the text with emphasis on the applications and computations in operations research. Complex mathematical concepts are effectively explained by means of carefully designed numerical examples, essentially eliminating the need for formal mathematical proofs. The integration of practical applications of software allows students to test concepts that could not, otherwise, be presented effectively. The book includes fully analyzed practical situations and each chapter concludes with summary applications borrowed from published case studies. Key Features AMPL, the powerful commercial modeling language, has been integrated throughout the book using numerous examples ranging from linear- and network- to integer- and nonlinear programming. An Excel-based combined nearest neighbor-reversal heuristic is presented for the traveling salesperson problem Markov chains treatment has been expanded. Approximately 50 end-of-chapter mini-cases of real-life situations are included. Each chapter starts with a study guide that facilitates the understanding of the material and the effective use of the accompanying software Excel spreadsheet implementations are used extensively throughout the book. The use of Excel Solver has been expanded significantly throughout the book, particularly in the areas of linear, network, integer, and nonlinear programming Table of Contents What is Operations Research? Modeling with Linear Programming The Simplex Method and Sensitivity Analysis Duality and Post-Optimal Analysis Transportation Model and its Variants Network Models Advanced Linear Programming Goal Programming Integer Linear Programming Deterministic Dynamic Programming Deterministic Inventory Models Review of Basic Probability Decision Analysis and Games Probabilistic Inventory Models Queueing Systems Simulation Modeling Markov Chains Classical Optimization Theory Nonlinear Programming Algorithms Additional Network and LP Algorithms Forecasting Models Probabilistic Dynamic Programming Markovian Decision Process Case Analysis