Operations Research: An Introduction, Global Edition, 11th edition

Published by Pearson (13 September 2024) © 2024

  • Hamdy A. Taha University of Arkansas
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Title overview

A balanced combination of theory, applications and computations

Operations Research: An Introduction helps you learn the basics of operating research (OR). It focuses on algorithmic and practical implementation of OR techniques. Easy-to-understand numerical examples explain often difficult math concepts, helping you grasp the foundational idea without getting stuck on complex theorems or notations. Full case studies and math-free anecdotes show how algorithms are used in real-life applications.

The 11th Edition introduces analytics, artificial intelligence, and machine learning topics that strengthen and streamline the decision-making processes involved in OR. New stories, 3 new chapters, new case studies and sections provide an up-to-date introduction to the field of OR.

Table of contents

  • Overview of Operations Research, Analytics, and AI in Decision Making
  • 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
  • Stochastic Linear Programming
  • Integer Linear Programming
  • Heuristic and Constraint Programming
  • Traveling Salesperson Problem (TSP)
  • Dynamic Programming (DP)
  • Inventory Modeling
  • Yield Management (YM)
  • Decision Analysis and Games
  • Markov Chains
  • Markovian Decision Process
  • Queuing Systems
  • Discrete Event and Monte Carlo Simulations
  • Classical Optimization Theory
  • Nonlinear Programming Algorithms
  • Case Analysis
  • Appendices
  • Statistical Tables
  • Partial Answers to Selected Problems
  • AMPL Modeling Language
  • Review of Vectors and Matrices
  • Review of Basic Probability
  • Forecasting Models

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