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Note: A local‐search heuristic for large set‐covering problems

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  • Larry W. Jacobs
  • Michael J. Brusco

Abstract

In this note we describe a local‐search heuristic (LSH) for large non‐unicost set‐covering problems (SCPs). The new heuristic is based on the simulated annealing algorithm and uses an improvement routine designed to provide low‐cost solutions within a reasonable amount of CPU time. The solution costs associated with the LSH compared very favorably to the best previously published solution costs for 20 large SCPs taken from the literature. In particular, the LSH yielded new benchmark solutions for 17 of the 20 test problems. We also report that, for SCPs where column cost is correlated with column coverage, the new heuristic provides solution costs competitive with previously published results for comparable problems. © 1995 John Wiley & Sons, Inc.

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  • Larry W. Jacobs & Michael J. Brusco, 1995. "Note: A local‐search heuristic for large set‐covering problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(7), pages 1129-1140, October.
    • Handle: RePEc:wly:navres:v:42:y:1995:i:7:p:1129-1140
    DOI: 10.1002/1520-6750(199510)42:73.0.CO;2-M
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    2. Vié, Marie-Sklaerder & Zufferey, Nicolas & Cordeau, Jean-François, 2019. "Solving the Wire-Harness Design Problem at a European car manufacturer," European Journal of Operational Research, Elsevier, vol. 272(2), pages 712-724.

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