Abstract
A hybrid Differential Evolution algorithm with double population was proposed for 0-1 knapsack problem. The two populations play different roles during the process of evolution with the floating-point population as an engine while the binary population guiding the search direction. Each gene of every chromosome in the floating-point encoding population is restricted to the range [-1, 1], while each gene of every chromosome in the binary encoding population is zero or one. A new mapping operation based on sign function was proposed to generate the binary population from the floating-point population. And a local refining operation called discarding operation was employed in the new algorithm to fix up the solutions which are infeasible. Three benchmarks of 0-1 knapsack problem with different sizes were used to verify the new algorithm and the performance of the new algorithm was also compared with that of other evolutionary algorithms. The simulation results show it is an effective and efficient way for the 0-1 Knapsack problem.
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References
Storn, R., Price, K.: Differential Evolution-A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization 11, 241–354 (1997)
Chiou, J.P.: Variable scaling hybrid differential evolution for large scale economic dispatch problems. Electric Power System Research 77, 212–218 (2007)
Abbass, H.A.: An evolutionary artificial neural networks approach for breast cancer diagnosis. Artificial Intelligence in Medicine 25, 265–281 (2002)
Aydin, S., Temeltas, H.: Fuzzy-differential evolution algorithm for planning time optimal trajectories of a unicycle mobile robot on a predefined path. Advanced Robotics 18, 725–748 (2004)
Cruz, L., Willligenburg, V., Straten, G.: Multimodal optimal control problem. Applied Soft Computing 3, 97–122 (2003)
Kaelo, P., Ali, M.: A numerical study of some modified differential evolution algorithms. European Journal of Operation Research 169, 1176–1184 (2006)
Yan, L., Chao, L.: A Schema-Guiding Evolutionary Algorithm for 0-1 Knapsack Problem. Iacsit-sc. In: 2009 International Association of Computer Science and Information Technology –Spring Conference, pp. 160–164. IEEE Press, Singapore (2009)
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Deng, C., Zhao, B., Yang, Y., Deng, A. (2010). Hybrid Differential Evolution for Knapsack Problem. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13495-1_62
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DOI: https://doi.org/10.1007/978-3-642-13495-1_62
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