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The Design, Analysis and Implementation of Heuristics

Author

Listed:
  • Marshall L. Fisher

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6366)

  • Alexander H. G. Rinnooy Kan

    (Econometric Institute, Erasmus Universiteit Rotterdam, Rotterdam, The Netherlands)

Abstract

The 1950s were a flourishing period for Management Science that saw many practical successfully attacked through the application of inelegant but effective heuristics. In the 1960s, attention turned to optimization, leading to the development of algorithms that employed more sophisticated mathematical constructs. While these algorithms were a significant research achievement, they failed to provide for reliable solutions to many problems. The 1970s seem to have been a period of soul searching in which computational complexity results were discovered, providing evidence that those who failed to develop effective optimization algorithms should not be discouraged, since the problems were probably intractable anyway. As a consequence, some of the intellectual energy that had been devoted to optimization began to be directed to the study of heuristics, but from an enriched perspective that emphasized theoretical performance analysis, both worth case and probabilistic.

Suggested Citation

  • Marshall L. Fisher & Alexander H. G. Rinnooy Kan, 1988. "The Design, Analysis and Implementation of Heuristics," Management Science, INFORMS, vol. 34(3), pages 263-265, March.
    • Handle: RePEc:inm:ormnsc:v:34:y:1988:i:3:p:263-265
    DOI: 10.1287/mnsc.34.3.263
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    Citations

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    Cited by:

    1. Matsatsinis, Nikolaos F., 2004. "Towards a decision support system for the ready concrete distribution system: A case of a Greek company," European Journal of Operational Research, Elsevier, vol. 152(2), pages 487-499, January.
    2. Amini, Mohammad M. & Racer, Michael & Ghandforoush, Parviz, 1998. "Heuristic sensitivity analysis in a combinatoric environment: An exposition and case study," European Journal of Operational Research, Elsevier, vol. 108(3), pages 604-617, August.
    3. Jihong Yan & Wenliang Cheng & Chengyu Wang & Jun Liu & Ming Gao & Aoying Zhou, 2015. "Optimizing word set coverage for multi-event summarization," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 996-1015, November.
    4. Ablanedo-Rosas, José H. & Rego, César, 2010. "Surrogate constraint normalization for the set covering problem," European Journal of Operational Research, Elsevier, vol. 205(3), pages 540-551, September.
    5. Jain, A. S. & Meeran, S., 1999. "Deterministic job-shop scheduling: Past, present and future," European Journal of Operational Research, Elsevier, vol. 113(2), pages 390-434, March.
    6. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.

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