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An indirect genetic algorithm for set covering problems

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  • U Aickelin

    (University of the West of England)

Abstract

This paper presents a new type of genetic algorithm for the set covering problem. It differs from previous evolutionary approaches first because it is an indirect algorithm, ie the actual solutions are found by an external decoder function. The genetic algorithm itself provides this decoder with permutations of the solution variables and other parameters. Second, it will be shown that results can be further improved by adding another indirect optimisation layer. The decoder will not directly seek out low cost solutions but instead aims for good exploitable solutions. These are then post-optimised by another hill-climbing algorithm. Although seemingly more complicated, we will show that this three-stage approach has advantages in terms of solution quality, speed and adaptability to new types of problems over more direct approaches. Extensive computational results are presented and compared to the latest evolutionary and other heuristic approaches to the same data instances.

Suggested Citation

  • U Aickelin, 2002. "An indirect genetic algorithm for set covering problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(10), pages 1118-1126, October.
    • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:10:d:10.1057_palgrave.jors.2601317
    DOI: 10.1057/palgrave.jors.2601317
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    Citations

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    Cited by:

    1. Yourim Yoon & Yong-Hyuk Kim, 2020. "Gene-Similarity Normalization in a Genetic Algorithm for the Maximum k -Coverage Problem," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    2. U Aickelin & E K Burke & J Li, 2007. "An estimation of distribution algorithm with intelligent local search for rule-based nurse rostering," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1574-1585, December.
    3. Naji-Azimi, Zahra & Toth, Paolo & Galli, Laura, 2010. "An electromagnetism metaheuristic for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 205(2), pages 290-300, September.
    4. F J Vasko & P J Knolle & D S Spiegel, 2005. "An empirical study of hybrid genetic algorithms for the set covering problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1213-1223, October.
    5. Eva K. Lee & Chien-Hung Chen & Ferdinand Pietz & Bernard Benecke, 2009. "Modeling and Optimizing the Public-Health Infrastructure for Emergency Response," Interfaces, INFORMS, vol. 39(5), pages 476-490, October.
    6. Eva K. Lee & Ferdinand Pietz & Bernard Benecke & Jacquelyn Mason & Greg Burel, 2013. "Advancing Public Health and Medical Preparedness with Operations Research," Interfaces, INFORMS, vol. 43(1), pages 79-98, February.
    7. H Younies & G O Wesolowsky, 2007. "Planar maximal covering location problem under block norm distance measure," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 740-750, June.
    8. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    9. Uwe Aickelin & Jingpeng Li, 2007. "An estimation of distribution algorithm for nurse scheduling," Annals of Operations Research, Springer, vol. 155(1), pages 289-309, November.
    10. Lan, Guanghui & DePuy, Gail W. & Whitehouse, Gary E., 2007. "An effective and simple heuristic for the set covering problem," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1387-1403, February.
    11. repec:spr:compst:v:74:y:2011:i:3:p:281-310 is not listed on IDEAS
    12. Yagiura, Mutsunori & Kishida, Masahiro & Ibaraki, Toshihide, 2006. "A 3-flip neighborhood local search for the set covering problem," European Journal of Operational Research, Elsevier, vol. 172(2), pages 472-499, July.
    13. Dimitris Bertsimas & Dan A. Iancu & Dmitriy Katz, 2013. "A New Local Search Algorithm for Binary Optimization," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 208-221, May.
    14. Ibrahim, Walid & El-Sayed, Hesham & El-Chouemie, Amr & Amer, Hoda, 2009. "An adaptive heuristic algorithm for VLSI test vectors selection," European Journal of Operational Research, Elsevier, vol. 199(3), pages 630-639, December.

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