Operations Research A Practical Introduction, 2nd Edition
©2018 |CRC | Taylor Francis Group
Operations Research: A Practical Introduction is just that: a hands-on approach to the field of operations research (OR) and a useful guide for using OR techniques in scientific decision making, design, analysis and management. The text accomplishes two goals. First, it provides readers with an introduction to standard mathematical models and algorithms. Second, it is a thorough examination of practical issues relevant to the development and use of computational methods for problem solving.
Many students of various disciplines such as mathematics, economics, industrial engineering and computer science often take one course in operations research. This book is written to provide a succinct and efficient introduction to the subject for these students, while offering a sound and fundamental preparation for more advanced courses in linear and nonlinear optimization, and many stochastic models and analyses.
It provides relevant analytical tools for this varied audience and will also serve professionals, corporate managers, and technical consultants.
Introduction to Operations Research.
The Origins and Applications of Operations Research.
System Modeling Principles.
Algorithm Efficiency and Problem Complexity.
Optimality and Practicality.
Software for Operations Research.
Illustrative Applications.Linear Programming.
The Linear Programming Model.
The Art and Skill of Problem Formulation.
Preparation for the Simplex Method.
The Simplex Method.
Initial Solutions for General Constraints.
Information on the Tableau.
Duality and Sensitivity Analysis.
Revised Simplex and Computational Efficiency.
Software for Linear Programming.
Graphs and Networks: Preliminary Definitions.
Maximum Flow in Networks.
inimum Cost Network Flow Problems.
Shortest Path Problems.
oftware for Network Analysis.
Typical Integer Programming Problems.
Zero-One Model Formulations. Branch-and-Bound.
Cutting Planes and Facets.
Software for Integer Programming.
Preliminary Notation and Concepts.
Software for Nonlinear Optimization.
First Passage Probabilities.
Properties of the States in a Markov Process.
Expected First Passage Times.
Software for Markov Processes.
Basic Elements of Queueing Systems.
Arrival and Service Patterns.
Software for Queueing Models.
Simulation: Purposes and Applications.
Discrete Simulation Models.
Observations of Simulations.
Software for Simulation.
The Decision-Making Process.
An Introduction to Game Theory.
The Psychology of Decision-Making.
Software for Decision Analysis.
Heuristic and Metaheuristic Techniques for Optimization.
Local Improvement Heuristics.
Constraint Programming and Local Search.
Software for Metaheuristics.