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Finding Feasible Solutions to Hard Mixed-integer Programming Problems Using Hybrid Heuristics

  • Philipp M. Christophel
  • Leena Suhl
  • Uwe H. Suhl
Conference paper
Part of the Operations Research Proceedings book series (ORP, volume 2005)

Abstract

In current mixed-integer programming (MIP) solvers heuristics are used to find feasible solutions before the branch-and-bound or branchand-cut algorithm is applied to the problem. Knowing a feasible solution can improve the solutions found or the time to solve the problem very much. This paper discusses hybrid heuristics for this purpose. Hybrid in this context means that these heuristics use the branch-and-bound algorithm to search a smaller subproblem. Several possible hybrid heuristics are presented and computational results are given.

Keywords

Search Space Feasible Solution Linear Programming Relaxation Relaxation Solution Hybrid Heuristic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Philipp M. Christophel
    • 1
  • Leena Suhl
    • 1
  • Uwe H. Suhl
    • 2
  1. 1.DS&OR LabUniversity of PaderbornPaderborn
  2. 2.Institut für Produktion, Wirtschaftsinformatik und ORFreie Universität BerlinBerlin (Dahlem)

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