Published by Pearson (July 9, 2024) © 2024
Hamdy TahaOperations Research uses a balanced combination of theory, applications and computations to help 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.
- 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