Abstract
The set covering problem is a classical model in the subject of combinatorial optimization for service allocation, that consists in finding a set of solutions for covering a range of needs at the lowest possible cost. In this paper, we report various approximate methods to solve this problem, such as Cuckoo Search, Bee Colony, Firefly Optimization, and Electromagnetism-Like Algorithms. We illustrate experimental results of these metaheuristics for solving a set of 65 non-unicost set covering problems from the Beasley’s OR-Library.
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References
Akay, B., Karaboga, D.: Parameter tuning for the artificial bee colony algorithm. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS, vol. 5796, pp. 608–619. Springer, Heidelberg (2009)
Balas, E., Carrera, M.C.: Carnegie-Mellon University. Management Sciences Research Group. A Dynamic Subgradient-based Branch and Bound Procedure for Set Covering. Management sciences research report. Management Sciences Research Group, Graduate School of Industrial Administration, Carnegie Mellon University (1992)
Beasley, J.E.: http://www.brunel.ac.uk/mastjjb/jeb/info.html (last visited on January 30, 2015)
Beasley, J.E., Chu, P.C.: A genetic algorithm for the set covering problem. European Journal of Operational Research 94(2), 392–404 (1996)
Birbil, S.I., Fang, S.-C.: An electromagnetism-like mechanism for global optimization. Journal of Global Optimization 25(3), 263–282 (2003)
Brusco, M.J., Jacobs, L.W., Thompson, G.M.: A morphing procedure to supplement a simulated annealing heuristic for cost and coverage correlated setcovering problems. Annals of Operations Research 86, 611–627 (1999)
Caprara, A., Fischetti, M., Toth, P.: A heuristic method for the set covering problem. Operations Research 47, 730–743 (1995)
Caprara, A., Toth, P., Fischetti, M.: Algorithms for the set covering problem. Annals of Operations Research 98(1–4), 353–371 (2000)
Caserta, M.: Tabu search-based metaheuristic algorithm for large-scale set covering problems. In: Doerner, K.F., Gendreau, M., Greistorfer, P., Gutjahr, W., Hartl, R.F., Reimann, M. (eds.) Metaheuristics. Operations Research/Computer Science Interfaces Series, vol. 39, pp. 43–63. Springer, US (2007)
Ceria, S., Nobili, P., Sassano, A.: A Lagrangian-based heuristic for large-scale set covering problems. Mathematical Programming 81(2), 215–228 (1998)
Chandrasekaran, K., Simon, S.P., Padhy, N.P.: Binary real coded firefly algorithm for solving unit commitment problem. Information Sciences 249, 67–84 (2013)
Chvatal, V.: A greedy heuristic for the set-covering problem. Mathematics of Operations Research 4(3), 233–235 (1979)
Crawford, B., Castro, C., Monfroy, E., Soto, R., Palma, W., Paredes, F.: Dynamic selection of enumeration strategies for solving constraint satisfaction problems. Romanian Journal of Information Science and Technology 15(2), 106–128 (2013)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman & Co., New York (1979)
Karaboga, D., Akay, B.: A survey: algorithms simulating bee swarm intelligence. Artificial Intelligence Review 31(1–4), 61–85 (2009)
Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm. Journal of Global Optimization 39(3), 459–471 (2007)
Kiran, M.S., Gndz, M.: Xor-based artificial bee colony algorithm for binary optimization. Turkish Journal of Electrical Engineering and Computer Sciences 21(suppl. 2), 2307–2328 (2013); cited By 2
Mirjalili, S., Hashim, S., Taherzadeh, G., Mirjalili, S.Z., Salehi, S.: A study of different transfer functions for binary version of particle swarm optimization. In: GEM 2011. CSREA Press (2011)
Pezzella, F., Faggioli, E.: Solving large set covering problems for crew scheduling. Top 5(1), 41–59 (1997)
Vasko, F.J., Wilson, G.R.: Using a facility location algorithm to solve large set covering problems. Operations Research Letters 3(2), 85–90 (1984)
Vasko, F.J., Wolf, F.E., Stott, K.L.: Optimal selection of ingot sizes via set covering. Oper. Res. 35(3), 346–353 (1987)
Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press (2008)
Yang, X.-S.: Firefly algorithms for multimodal optimization. In: Watanabe, O., Zeugmann, T. (eds.) SAGA 2009. LNCS, vol. 5792, pp. 169–178. Springer, Heidelberg (2009)
Yang, X.-S.: Bat algorithm and cuckoo search: a tutorial. In: Yang, X.-S. (ed.) Artificial Intelligence, Evolutionary Computing and Metaheuristics. SCI, vol. 427, pp. 421–434. Springer, Heidelberg (2013)
Yang, X.S., Deb, S.: Cuckoo Search via Levy Flights. ArXiv e-prints (March 2010)
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Soto, R. et al. (2015). Comparing Cuckoo Search, Bee Colony, Firefly Optimization, and Electromagnetism-Like Algorithms for Solving the Set Covering Problem. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9155. Springer, Cham. https://doi.org/10.1007/978-3-319-21404-7_14
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DOI: https://doi.org/10.1007/978-3-319-21404-7_14
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