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Mathematical programming based heuristics for the 0–1 MIP: a survey

Author

Listed:
  • Saïd Hanafi

    (LAMIH UMR CNRS 8201 - Université de Valenciennes)

  • Raca Todosijević

    (LAMIH UMR CNRS 8201 - Université de Valenciennes)

Abstract

The 0–1 mixed integer programming problem is used for modeling many combinatorial problems, ranging from logical design to scheduling and routing as well as encompassing graph theory models for resource allocation and financial planning. This paper provides a survey of heuristics based on mathematical programming for solving 0–1 mixed integer programs (MIP). More precisely, we focus on the stand-alone heuristics for 0–1 MIP as well as those heuristics that use linear programming techniques or solve a series of linear programming models or reduced problems, deduced from the initial one, in order to produce a high quality solution of a considered problem. Our emphasis will be on how mathematical programming techniques can be used for approximate problem solving, rather than on comparing performances of heuristics.

Suggested Citation

  • Saïd Hanafi & Raca Todosijević, 2017. "Mathematical programming based heuristics for the 0–1 MIP: a survey," Journal of Heuristics, Springer, vol. 23(4), pages 165-206, August.
    • Handle: RePEc:spr:joheur:v:23:y:2017:i:4:d:10.1007_s10732-017-9336-y
    DOI: 10.1007/s10732-017-9336-y
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    Cited by:

    1. Charly Robinson La Rocca & Jean-François Cordeau & Emma Frejinger, 2024. "One-Shot Learning for MIPs with SOS1 Constraints," SN Operations Research Forum, Springer, vol. 5(3), pages 1-28, September.

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