1st Edition

Operations Research A Practical Introduction

By Michael W. Carter, Camille C. Price Copyright 2001

    Students with diverse backgrounds will face a multitude of decisions in a variety of engineering, scientific, industrial, and financial settings. They will need to know how to identify problems that the methods of operations research (OR) can solve, how to structure the problems into standard mathematical models, and finally how to apply or develop computational tools to solve the problems.

    Perfect for any one-semester course in OR, Operations Research: A Practical Introduction answers all of these needs. In addition to providing a practical introduction and guide to using OR techniques, it includes a timely examination of innovative methods and practical issues related to the development and use of computer implementations. It provides a sound introduction to the mathematical models relevant to OR and illustrates the effective use of OR techniques with examples drawn from industrial, computing, engineering, and business applications.

    Many students will take only one course in the techniques of Operations Research. Operations Research: A Practical Introduction offers them the greatest benefit from that course through a broad survey of the techniques and tools available for quantitative decision making. It will also encourage other students to pursue more advanced studies and provides you a concise, well-structured, vehicle for delivering the best possible overview of the discipline.

    The Origins and Applications of Operations Research
    System Modeling Principles
    Algorithm Efficiency and Problem Complexity
    Optimality and Practicality
    Guide to Software Tools

    The Linear Programming Model
    The Art of Problem Formulation
    Graphical Solution of Linear Programming Problems
    Preparation for the Simplex Method
    The Simplex Method
    Initial Solutions for General Constraints
    Information in the Tableau
    Duality and Sensitivity Analysis
    Revised Simplex and Computational Efficiency
    Guide to Software Tools
    Illustrative Applications

    Graphs and Networks: Preliminary Definitions
    Maximum Flow in Networks
    Minimum Cost Network Flow Problems
    Network Connectivity
    Shortest Path Problems
    Dynamic Programming
    Project Management
    Guide to Software Tools
    Illustrative Applications

    Fundamental Concepts
    Typical Integer Programming Problems
    Zero-One Model Formulations
    Cutting Planes and Facets
    Cover Inequalities
    Lagrangian Relaxation
    Column Generation
    Guide to Software Tools
    Illustrative Applications

    Preliminary Notation and Concepts
    Unconstrained Optimization
    Constrained Optimization
    Guide to Software Tools
    Illustrative Applications

    State Transitions
    State Probabilities
    First Passage Probabilities
    Properties of the States in a Markov Process
    Steady-State Analysis
    Expected First Passage Times
    Absorbing Chains
    Guide to Software Tools
    Illustrative Applications

    Basic Elements of Queuing Systems
    Arrival and Service Patterns
    Analysis of Simple Queuing Systems
    Guide to Software Tools
    Illustrative Applications

    Simulation: Purposes and Applications
    Discrete Simulation Models
    Observations of Simulations
    Guide to Software Tools
    Illustrative Applications

    The Decision Making Process
    An Introduction to Game Theory
    Decision Trees
    Utility Theory
    The Psychology of Decision Making
    Guide to Software Tools
    Illustrative Applications

    Local Improvement Heuristics
    Optimization by Simulated Annealing
    Parallel Annealing
    Genetic Algorithms
    Neural Networks
    Guide to Software Tools
    Illustrative Applications

    APPENDIX: Review of Essential Mathematics


    Michael W. Carter and Camille C. Price

    "The chapter on heuristics techniques is particularly welcome."
    Short Book Reviews, Vol. 21, No. 2, August, 2001