Abstract
A particle swarm optimization algorithm based on adaptive mutation and P systems is proposed to overcome trapping in local optimum solution and low optimization precision in this paper. At the same time, the proposed algorithm is investigated in experiments which are based on the function optimization of micro-grid’s economic operation. Furthermore, the feasibility and effectiveness of the proposed algorithm are showed in the experimental results.
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Liu, T., Wang, J., Sun, Z., Luo, J., He, T., Chen, K. (2014). An Improved Particle Swarm Optimization and Its Application for Micro-grid Economic Operation Optimization. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_44
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DOI: https://doi.org/10.1007/978-3-662-45049-9_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45048-2
Online ISBN: 978-3-662-45049-9
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