Abstract
In this paper, an improved particle swarm optimization (IPSO) algorithm is presented to solve RCP Scheduling Problem. Firstly, a mapping is created between the feasible schedule and the position of the particle, then the IPSO begin to search the global best and the local best until the stop criteria is satisfied. A case study is presented and a comparison is made between IPSO and some traditional heuristic methods. Results show that the IPSO algorithm is more satisfying than those of the heuristic methods in terms of feasibility and efficiency.
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Wang, Q., Qi, J. (2009). Improved Particle Swarm Optimization for RCP Scheduling Problem. In: Wang, H., Shen, Y., Huang, T., Zeng, Z. (eds) The Sixth International Symposium on Neural Networks (ISNN 2009). Advances in Intelligent and Soft Computing, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01216-7_6
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DOI: https://doi.org/10.1007/978-3-642-01216-7_6
Publisher Name: Springer, Berlin, Heidelberg
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