Annals of Operations Research

, Volume 5, Issue 2, pp 395–411 | Cite as

Integrating modeling, algorithm design, and computational implementation to solve a large-scale non-linear mixed integer programming problem

  • F. Glover
  • D. Klingman
  • N. Phillips
  • G. T. Ross
Mathematical Programming
  • 56 Downloads

Abstract

This paper describes the formulation of a nonlinear mixed integer programming model for a large-scale product development and distribution problem and the design and computational implementation of a special purpose algorithm to solve the model. The results described demonstrate that integrating the art of modeling with the sciences of solution methodology and computer implementation provides a powerful approach for attacking difficult problems. The efforts described here were successful because they capitalized on the wealth of existing modeling technology and algorithm technology, the availability of efficient and reliable optimization, matrix generation and graphics software, and the speed of large-scale computer hardware. The model permitted the combined use of decomposition, general linear programming and network optimization within a branch and bound algorithm to overcome mathematical complexity. The computer system reliably found solutions with considerably better objective function values 30 to 50 times faster than had been achieved using general purpose optimization software alone. Throughout twenty months of daily use, the system was credited with providing insights and suggesting strategies that led to very large dollar savings.

Keywords and phrases

Nonlinear programming decomposition branch and bound network transportation mixed integer programming 

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Copyright information

© J.C. Baltzer A.G., Scientific Publishing Company 1986

Authors and Affiliations

  • F. Glover
    • 1
  • D. Klingman
    • 2
  • N. Phillips
    • 3
  • G. T. Ross
    • 4
  1. 1.Department of Management ScienceUniversity of ColoradoBoulderUSA
  2. 2.David Bruton, Jr., Centennial Chain in Business Decision Support SystemsUniversity of Texas at AustinAustinUSA
  3. 3.Department of Operations ResearchUniversity of Texas at AustinAustinUSA
  4. 4.Production and Distribution Planning SystemsAnalysis, Research, and Computation, Inc.AustinUSA

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