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A Memetic Approach for the Unicost Set Covering Problem

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Learning and Intelligent Optimization (LION 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12096))

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Abstract

The Unicost Set Covering Problem (USCP) is a well-known \(\mathcal {NP}\)-hard combinatorial optimization problem. This paper presents a memetic algorithm that combines and adapts the Hybrid Evolutionary Algorithm in Duet (HEAD) and the Row Weighting Local Search (RWLS) to solve the USCP. The former is a memetic approach with a population of only two individuals which was originally developed to tackle the graph coloring problem. The latter is a heuristic algorithm designed to solve the USCP by using a smart weighting scheme that prevents early convergence and guides the algorithm toward interesting sets. RWLS has been shown to be one of the most effective algorithm for the USCP. In the proposed approach, RWLS is modified to be efficiently used as the local search of HEAD (for exploitation purpose) on the one hand, and also to be used as the crossover (for exploration purpose) on the other hand. The HEAD framework is also adapted to take advantage of the information provided by the weighting scheme of RWLS. The proposed memetic algorithm is compared to RWLS on 98 widely-used benchmark instances (87 from the OR-Library and 11 derived from Steiner triple systems). The experimental study reports competitive results and the proposed algorithm improves the best known solutions for 8 instances.

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Notes

  1. 1.

    https://services-numeriques.unistra.fr/les-services-aux-usagers/hpc.html (french).

References

  1. Balas, E.: A class of location, distribution and scheduling problems: modeling and solution methods. In: Proceedings of the Chinese-U.S. Symposium on Systems Analysis. Wiley Series on Systems Engineering and Analysis. Wiley (1983). ISBN 978-0-471-87093-7

    Google Scholar 

  2. Balas, E., Ho, A.: Set covering algorithms using cutting planes, heuristics, and subgradient optimization: a computational study. In: Padberg, M.W. (ed.) Combinatorial Optimization. MATHPROGRAMM, vol. 12, pp. 37–60. Springer, Heidelberg (1980). https://doi.org/10.1007/BFb0120886. ISBN 978-3-642-00802-3

    Chapter  MATH  Google Scholar 

  3. Beasley, J.E.: A Lagrangian heuristic for set-covering problems. Naval Res. Logist. 37(1), 151–164 (1990). https://doi.org/10.1002/1520-6750(199002)37:1<151::AID-NAV3220370110>3.0.CO;2-2

    Article  MathSciNet  MATH  Google Scholar 

  4. Beasley, J.E.: OR-library: distributing test problems by electronic mail. J. Oper. Res. Soc. 41(11), 1069–1072 (1990). https://doi.org/10.1057/jors.1990.166

    Article  Google Scholar 

  5. Beasley, J.: An algorithm for set covering problem. Eur. J. Oper. Res. 31(1), 85–93 (1987). https://doi.org/10.1016/0377-2217(87)90141-X

    Article  MathSciNet  MATH  Google Scholar 

  6. Boschetti, M., Maniezzo, V.: A set covering based matheuristic for a real-world city logistics problem. Int. Trans. Oper. Res. 22(1), 169–195 (2015). https://doi.org/10.1111/itor.12110

    Article  MathSciNet  MATH  Google Scholar 

  7. Brévilliers, M., Lepagnot, J., Idoumghar, L., Rebai, M., Kritter, J.: Hybrid differential evolution algorithms for the optimal camera placement problem. J. Syst. Inf. Technol. (2018). https://doi.org/10.1108/JSIT-09-2017-0081

  8. Caprara, A., Fischetti, M., Toth, P.: A heuristic method for the set covering problem. Oper. Res. (1999). https://doi.org/10.1287/opre.47.5.730

    Article  MathSciNet  MATH  Google Scholar 

  9. Christofides, N., Korman, S.: A computational survey of methods for the set covering problem. Manag. Sci. 21(5), 591–599 (1975). https://doi.org/10.2307/2630042

    Article  MathSciNet  MATH  Google Scholar 

  10. Ding, J., Lü, Z., Li, C.-M., Shen, L., Xu, L., Glover, F.: A two-individual based evolutionary algorithm for the flexible job shop scheduling problem. Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, no. 01, pp. 2262–2271 (2019). https://doi.org/10.1609/aaai.v33i01.33012262

  11. Farahani, R.Z., Asgari, N., Heidari, N., Hosseininia, M., Goh, M.: Covering problems in facility location: a review. Comput. Ind. Eng. 62(1), 368–407 (2012). https://doi.org/10.1016/j.cie.2011.08.020

    Article  Google Scholar 

  12. Fulkerson, D.R., Nemhauser, G.L., Trotter, L.E.: Two computationally difficult set covering problems that arise in computing the 1-width of incidence matrices of Steiner triple systems. In: Balinski, M.L. (ed.) Approaches to Integer Programming. MATHPROGRAMM, vol. 2, pp. 72–81. Springer, Heidelberg (1974). https://doi.org/10.1007/BFb0120689. ISBN 978-3-642-00740-8

    Chapter  Google Scholar 

  13. Galinier, P., Hao, J.-K.: Hybrid evolutionary algorithms for graph coloring. J. Comb. Optim. 3(4), 379–397 (1999). https://doi.org/10.1023/A:1009823419804

    Article  MathSciNet  MATH  Google Scholar 

  14. Gao, C., Yao, X., Weise, T., Li, J.: An efficient local search heuristic with row weighting for the unicost set covering problem. Eur. J. Oper. Res. 246(3), 750–761 (2015). https://doi.org/10.1016/j.ejor.2015.05.038

    Article  MathSciNet  MATH  Google Scholar 

  15. Garey, M.R., Johnson, D.S.: Computers and Intractability; A Guide to the Theory of NP-Completeness. W. H. Freeman & Co. (1990). http://dl.acm.org/citation.cfm?id=574848

  16. Grossman, T., Wool, A.: Computational experience with approximation algorithms for the set covering problem. Eur. J. Oper. Res. 101(1), 81–92 (1997). https://doi.org/10.1016/S0377-2217(96)00161-0

    Article  MATH  Google Scholar 

  17. Hertz, A., de Werra, D.: Using tabu search techniques for graph coloring. Computing 39(4), 345–351 (1987). https://doi.org/10.1007/BF02239976

    Article  MathSciNet  MATH  Google Scholar 

  18. Karp, R.M.: Reducibility among combinatorial problems. In: Miller, R.E., Thatcher, J.W., Bohlinger, J.D. (eds.) Complexity of Computer Computations. The IBM Research Symposia Series, pp. 85–103. Springer, Boston (1972). https://doi.org/10.1007/978-1-4684-2001-2_9. ISBN 978-1-4684-2001-2

    Chapter  Google Scholar 

  19. Kritter, J., Brévilliers, M., Lepagnot, J., Idoumghar, L.: On the optimal placement of cameras for surveillance and the underlying set cover problem. Appl. Soft Comput. 74, 133–153 (2019). https://doi.org/10.1016/j.asoc.2018.10.025

    Article  Google Scholar 

  20. Moalic, L., Gondran, A.: The sum coloring problem: a memetic algorithm based on two individuals. In: 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 1798–1805 (2019). https://doi.org/10.1109/CEC.2019.8789927

  21. Moalic, L., Gondran, A.: Variations on memetic algorithms for graph coloring problems. J. Heuristics 24(1), 1–24 (2018). https://doi.org/10.1007/s10732-017-9354-9

    Article  Google Scholar 

  22. Yelbay, B., Birbil, Şİ., Bülbül, K.: The set covering problem revisited: an empirical study of the value of dual information. J. Ind. Manag. Optim. 11, 575 (2015). https://doi.org/10.3934/jimo.2015.11.575

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Laurent Moalic .

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Pinard, M., Moalic, L., Brévilliers, M., Lepagnot, J., Idoumghar, L. (2020). A Memetic Approach for the Unicost Set Covering Problem. In: Kotsireas, I., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2020. Lecture Notes in Computer Science(), vol 12096. Springer, Cham. https://doi.org/10.1007/978-3-030-53552-0_23

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