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Discrete Optimizing Solution Procedures for Linear and Nonlinear Integer Programming Problems

Author

Listed:
  • Stanley Reiter

    (Purdue University)

  • Donald B. Rice

    (Purdue University)

Abstract

We present a method for approximating the solution of mixed integer non-concave programming problems in bounded variables. We present computational results for 39 test problems which suggest that the procedure offers a practical useful way of approximating solutions of programming problems of the type tested. We have also discovered an apparent regularity in the distribution of local optima generated by the method; the method seems to generate Beta distributions in all problems for which results are available. This suggests interesting opportunities for further exploration.

Suggested Citation

  • Stanley Reiter & Donald B. Rice, 1966. "Discrete Optimizing Solution Procedures for Linear and Nonlinear Integer Programming Problems," Management Science, INFORMS, vol. 12(11), pages 829-850, July.
    • Handle: RePEc:inm:ormnsc:v:12:y:1966:i:11:p:829-850
    DOI: 10.1287/mnsc.12.11.829
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    Cited by:

    1. Mikhail Timonin, 2012. "Maximization of the Choquet integral over a convex set and its application to resource allocation problems," Annals of Operations Research, Springer, vol. 196(1), pages 543-579, July.
    2. Santhanam, Radhika & Kyparisis, George J., 1996. "A decision model for interdependent information system project selection," European Journal of Operational Research, Elsevier, vol. 89(2), pages 380-399, March.

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