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 engineering problems. In this paper, BBOA based Multidimensional Knapsack Problem (MKPBBOA) is proposed. The migration strategy is designed to solve the combination optimization problem. It is tested on standard MKPs. The experiment results show that MKPBBOA is good at solving such problems.
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References
Wallace, A.: The Geographical Distribution of Animals (Two Volumes). Adamant Media Corporation, Boston (2005)
Darwin, C.: The Origin of Species. Gramercy, New York, USA (1995)
Hanski, I., Gilpin, M.: Metapopulation Biology. Academic, New York (1997)
Simon, D.: Biogeography-based optimization. IEEE Transactions on Evolutionary Computation 12, 702–713 (2008)
Ergezer, M., Simon, D., Du, D.W.: Oppositional biogeography-based optimization. In: IEEE Conference on Systems, Man, and Cybernetics, San Antonio, TX, pp. 1035–1040. IEEE Press (2009)
Du, D., Simon, D., Ergezer, M.: Biogeography-based optimization combined with evolutionary strategy and immigration refusal. In: IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX, pp. 1023–1028. IEEE Press (2009)
Ma, H., Chen, X.: Equilibrium species counts and migration model tradeoffs for biogeography-based optimization. In: 48th IEEE Conference on Decision and Control, Shanghai, China, pp. 3306–3310 (2009)
Bhattacharya, A., Chattopadhyay, P.K.: Solving complex eeconomic load dispatch problems using bogeography-based otimization. Expert Systems with Applications 37, 3605–3615 (2010)
Qu, Z., Mo, H.W.: Research of Hybrid Biogeography Based Optimization and Clonal Selection Algorithm for Numerical Optimization. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011, Part I. LNCS, vol. 6728, pp. 390–399. Springer, Heidelberg (2011)
Mo, H.W., Xu, L.F.: Biogeography migration algorithm for traveling salesman problem. International Journal of Intelligent Computing and Cybernetics 4(3), 311–330 (2011)
Mo, H.W., Xu, Z.D.: Research of Biogeography-Based Multi-Objective Evolutionary Algorithm. Journal of Information Technology Research 4(2), 70–80 (2011)
Freville, A.: The multidimensional 0–1 knapsack problem: an overview. European Journal of Operational Research 155, 1–21 (2004)
Thiel, J., Voss, S.: Some experiences on solving multiconstraint zero–one knapsack problems with genetic algorithms. In: INFOR, vol. 32, pp. 226–242 (1994)
Chu, P., Beasley, D.: A genetic algorithm for the multiconstrained knapsack problem. Journal of Heuristics 4, 63–86 (1998)
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Mo, H., Li, Z., Zhang, L. (2012). Biogeography Based Optimization for Multi-Knapsack Problems. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_74
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DOI: https://doi.org/10.1007/978-3-642-31346-2_74
Publisher Name: Springer, Berlin, Heidelberg
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