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A Hybrid Method for Solving Large-Scale Supply Chain Problems

  • Steffen Wolf
  • Peter Merz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4446)

Abstract

The strategic supply chain design problem which allows capacity shifts and budget limitations can be formulated as a linear program. Since facilities are allowed to be opened or shut down during the planning horizon, this problem is in fact a mixed integer problem. Choosing the optimal set of facilities to serve the customer demands is an NP-hard combinatorial optimization problem. We present a hybrid method combining an evolutionary algorithm and LP based solvers for solving large-scale supply chain problems, which takes its power from filtering out infeasible solutions. The EA incorporating these filters is shown to be faster than the MIP solver ILOG CPLEX in most of the considered instances. For the remaining instances it finds feasible solutions much faster than the MIP solver.

Keywords

Evolutionary Algorithm Penalty Cost Facility Location Problem ILOG CPLEX Feasible Combination 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Steffen Wolf
    • 1
  • Peter Merz
    • 1
  1. 1.Distributed Algorithms Group, University of KaiserslauternGermany

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