Prentice Hall

Engineering

Browse available resources for Industrial Engineering:



Linear Programming
James P. Ignizio, University of Virginia
Tom M. Cavalier, Penn. State University

ISBN-10: 0131837575
ISBN-13: 9780131837577

Publisher: Prentice Hall
Copyright: 1994
Format: Paper; 666 pp
Published: 11/02/1993

Suggested retail price: $120.00
Buy from myPearsonStore

For senior/graduate-level courses in Linear Programming.

A comprehensive, modern introduction to the philosophies and procedures used in the modeling, solution, and analysis of linear programming problems.

  • addresses linear programming in general — with an emphasis on the development, presentation, and illustration (with examples) of the fundamentals necessary to model, solve, and analyze linear programs.
  • covers recent results with regard to alternative methods to the simplex algorithm — e.g., the affine scaling variants of the Karmarkar algorithm.
  • deals with the use of linear programming in information technology — e.g., as a means to analyze large amounts of data.
    • explores prediction/ forecasting, pattern classification/pattern recognition, clustering analysis, input-output analysis, and the design and training of neural networks — all achieved by means of linear programming

  • explores the important — but often neglected — area of heuristic programming and extends it to such currently popular heuristic methods as genetic algorithms, simulated annealing, and various related techniques that are often associated with the field of artificial intelligence.
  • addresses the topic of multiple objective optimization using an original, unified approach to both modeling and solution — the multiplex concept.
    • considers various multiobjective philosophies, their models, and their solution and analysis via a single algorithm

    • discusses and demonstrates how such problems may be solved via conventional linear programming algorithms and software



 1. Introduction and Overview.

I. CONVENTIONAL LINEAR PROGRAMMING.

 2. The (Conventional) Linear Programming Model.

 3. Foundations of the Simplex Method.

 4. The Simplex Method: Tableaux and Computation.

 5. Special Simplex Implementations.

 6. Duality and Sensitivity Analysis.

 7. Alternatives to the Simplex Algorithm.

 8. Applications of LP in Information Technology.

II. NETWORK AND INTEGER MODELS.

 9. The Network Simplex Method.

10. The Transportation and Assignment Problems.

11. Integer Programming.

12. Heuristic Programming - and AI.

III. MULTIOBJECTIVE OPTIMIZATION.

13. Multiobjective Optimization.

14. Multiobjective Models.

15. Multiplex Algorithm.

16. Duality and Sensitivity Analysis in Linear Multiplex.

17. Extensions of Multiplex.

Appendix: Review of Linear Algebra.

References.

Index.

Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students, contact your Pearson Higher Education representative for pricing and ordering information.

Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students contact your Pearson Higher Education representative.


Copyright ©2008 Pearson Education. All rights reserved. Legal Notice | Privacy Policy | Permissions