Abstract
Biogeography-Based Optimization Algorithm (BBOA) is a kind of new global optimization algorithm inspired by biogeography. It mimics the migration behavior of animals in nature to solve optimization and engineering problems. In this paper, BBOA for the Set Covering Problem (SCP) is proposed. SCP is a classic combinatorial problem from NP-hard list problems. It consist to find a set of solutions that cover a range of needs at the lowest possible cost following certain constraints. In addition, we provide a new feature for improve performance of BBOA, improving stagnation in local optimum. With this, the experiment results show that BBOA is very good at solving such problems.
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References
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. Series of Books in the Mathematical Sciences. Freeman, W. H (1979)
Balas, Egon, Carrera, Maria C.: A dynamic subgradient-based branch-and-bound procedure for set covering. Oper. Res. 44(6), 875–890 (1996)
Fisher, M.L., Kedia, P.: Optimal solution of set covering/partitioning problems using dual heuristics. Manage. Sci. 36(6), 674–688 (1990)
Simon, D.: Biogeography-based optimization. IEEE Trans. Evol. Comput. 12(6), 702–713 (2008)
Zhao, B., Deng, C., Yang, Y., Peng, Hu.: Novel binary biogeography-based optimization algorithm for the knapsack problem, pp. 217–224 (2012)
Beasley, J.E., Jornsten, K.: Enhancing an algorithm for set covering problems. Eur. J. Oper. Res. 58(2), 293 – 300 (1992) (Practical Combinatorial Optimization)
Lan, G., Depuy, G.W., Whitehouse G.E.: Discrete optimization an effective and simple heuristic for the set covering problem abstract (2005)
Eremeev, A.V., Kolokolov, A.A., Zaozerskaya, L.A.: A hybrid algorithm for set covering problem, pp. 123–129 (2000)
Monfroy, E., Crawford, B., Soto, R., Paredes, F., Palma, W.: A hybrid ant algorithm for the set covering problem. Int. J. Phys. Sci. 6, 4667–4673 (2011)
Crawford, B., Soto, R., Berrios, N., Johnson, F., Paredes, F.: Solving the set covering problem with binary cat swarm optimization. In: Advances in Swarm and Computational Intelligence. Lecture Notes in Computer Science, vol. 9140, pp. 41–48. Springer International Publishing (2015)
Crawford, B., Soto, R., Olea, C., Johnson, F., Paredes, F.: Binary bat algorithms for the set covering problem. In: 2015 10th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–4, June 2015
Soto, R., Crawford, B., Olivares, R., Barraza, J., Johnson, F., Paredes, F.: A binary cuckoo search algorithm for solving the set covering problem. 9108, 88–97 (2015)
Crawford, B., Soto, R., Cuesta, R., Paredes, F.: Application of the artificial bee colony algorithm for solving the set covering problem. Sci. World J. 2014(189164), 1–8 (2014)
Crawford, B., Soto, R., Olivares Suarez, M., Paredes, F., Johnson, F.: Binary firefly algorithm for the set covering problem. In: 2014 9th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–5, June 2014
Mudaliar, D.N., Modi, N.K.: Unraveling travelling salesman problem by genetic algorithm using m-crossover operator. In: 2013 International Conference on Signal Processing Image Processing Pattern Recognition (ICSIPR), pp. 127–130, Feb 2013
Mo, H., Xu, L.: Biogeography migration algorithm for traveling salesman problem. In: Advances in Swarm Intelligence, vol. 6145, pp. 405–414. Springer, Heidelberg (2010)
Ma, H., Simon, D.: Biogeography-based optimization with blended migration for constrained optimization problems. In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, pp. 417–418. ACM, New York, NY, USA (2010)
Naji-Azimi, Z., Toth, P., Galli, L.: An electromagnetism metaheuristic for the unicost set covering problem. Eur. J. Oper. Res. 205(2), 290–300 (2010)
Xu, Y., Kochenberger, G., Wang, H.: Pre-processing method with surrogate constraint algorithm for the set covering problem
Cuesta, R., Crawford, B., Soto, R., Paredes, F.: Application of the artificial bee colony algorithm for solving the set covering problem. Sci. World J. 4–6 (2014)
Acknowledgments
The author Broderick Crawford is supported by grant CONICYT/FONDE-CYT/REGULAR/1140897 and Ricardo Soto is supported by grant CONICYT/FONDECYT/INICIACION/11130459.
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Crawford, B., Soto, R., Riquelme, L., Olguín, E. (2016). Biogeography-Based Optimization Algorithm for Solving the Set Covering Problem. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Artificial Intelligence Perspectives in Intelligent Systems. Advances in Intelligent Systems and Computing, vol 464. Springer, Cham. https://doi.org/10.1007/978-3-319-33625-1_25
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DOI: https://doi.org/10.1007/978-3-319-33625-1_25
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