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Operations Research in Transportation Systems

Ideas and Schemes of Optimization Methods for Strategic Planning and Operations Management

  • Book
  • © 1998

Overview

Authors:
  1. Alexander S. Belenky
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Part of the book series: Applied Optimization (APOP, volume 20)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-viii
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  2. Introduction

    • Alexander S. Belenky
    Pages 1-11

  3. Mathematical Programming

    • Alexander S. Belenky
    Pages 13-90

  4. Discrete Optimization

    • Alexander S. Belenky
    Pages 91-124

  5. Transportation-Oriented Optimization

    • Alexander S. Belenky
    Pages 125-224

  6. Optimization under Uncertainty

    • Alexander S. Belenky
    Pages 225-283

  7. Optimal Control

    • Alexander S. Belenky
    Pages 285-308

  8. Optimization in Special Methods of Strategic Planning and Operations Management in Transportation Systems

    • Alexander S. Belenky
    Pages 309-324

  9. Mathematical Concepts and Notation Used for Formulating and Solving Optimization Problems of Strategic Planning and Operations Management in Transportation Systems

    • Alexander S. Belenky
    Pages 325-358

  10. Conclusion

    • Alexander S. Belenky
    Pages 359-363

  11. Back Matter

    Pages 365-440
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Keywords

About this book

The scientific monograph of a survey kind presented to the reader's attention deals with fundamental ideas and basic schemes of optimization methods that can be effectively used for solving strategic planning and operations manage­ ment problems related, in particular, to transportation. This monograph is an English translation of a considerable part of the author's book with a similar title that was published in Russian in 1992. The material of the monograph embraces methods of linear and nonlinear programming; nonsmooth and nonconvex optimization; integer programming, solving problems on graphs, and solving problems with mixed variables; rout­ ing, scheduling, solving network flow problems, and solving the transportation problem; stochastic programming, multicriteria optimization, game theory, and optimization on fuzzy sets and under fuzzy goals; optimal control of systems described by ordinary differential equations, partial differential equations, gen­ eralized differential equations (differential inclusions), and functional equations with a variable that can assume only discrete values; and some other methods that are based on or adjoin to the listed ones.

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