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Practical Bilevel Optimization

Algorithms and Applications

  • Book
  • © 1998

Overview

Authors:
  1. Jonathan F. Bard

    1. Graduate Program in Operations Research, Department of Mechanical Engineering, The University of Texas, Austin, USA

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Part of the book series: Nonconvex Optimization and Its Applications (NOIA, volume 30)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xii
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  2. Mathematical Programming

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Jonathan F. Bard
      Pages 3-16

    3. Linear Programming

      • Jonathan F. Bard
      Pages 17-75

    4. Integer Programming

      • Jonathan F. Bard
      Pages 76-136

    5. Nonlinear Programming

      • Jonathan F. Bard
      Pages 137-192

  3. Bilevel Programming

    1. Front Matter

      Pages 193-193
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    2. Linear Bilevel Programming: Continuous Variables

      • Jonathan F. Bard
      Pages 195-231

    3. Linear Bilevel Programming: Discrete Variables

      • Jonathan F. Bard
      Pages 232-268

    4. Convex Bilevel Programming

      • Jonathan F. Bard
      Pages 269-300

    5. General Bilevel Programming

      • Jonathan F. Bard
      Pages 301-360

    6. Heuristics

      • Jonathan F. Bard
      Pages 361-388

  4. Applications

    1. Front Matter

      Pages 389-389
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    2. Transportation Network Design

      • Jonathan F. Bard
      Pages 391-413

    3. Production Planning with Inexact Customer Demand

      • Jonathan F. Bard
      Pages 414-427

    4. Determining Price Support Levels for Biofuel Crops

      • Jonathan F. Bard
      Pages 428-454

  5. Back Matter

    Pages 455-476
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Keywords

About this book

The use of optimization techniques has become integral to the design and analysis of most industrial and socio-economic systems. Great strides have been made recently in the solution of large-scale problems arising in such areas as production planning, airline scheduling, government regulation, and engineering design, to name a few. Analysts have found, however, that standard mathematical programming models are often inadequate in these situations because more than a single objective function and a single decision maker are involved. Multiple objective programming deals with the extension of optimization techniques to account for several objective functions, while game theory deals with the inter-personal dynamics surrounding conflict. Bilevel programming, the focus of this book, is in a narrow sense the combination of the two. It addresses the problern in which two decision makers, each with their individual objectives, act and react in a noncooperative, sequential manner. The actions of one affect the choices and payoffs available to the other but neither player can completely dominate the other in the traditional sense.

Authors and Affiliations

  • Graduate Program in Operations Research, Department of Mechanical Engineering, The University of Texas, Austin, USA

    Jonathan F. Bard

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