Improving the responsiveness of NSGA-II using an adaptive mutation operator: a case study
by Alvaro Gomes, C. Henggeler Antunes, A. Gomes Martins
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 2, No. 1, 2010

Abstract: This paper presents a comparative analysis of the results obtained with two different implementations of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) in the framework of load management activities in power systems. The multiobjective real-world problem deals with the identification and the selection of control strategies to be applied to groups of loads aimed at reducing maximum power demand (PD), maximising profits and minimising user discomfort. It is shown that the algorithm performance is improved when the NSGA-II mutation operator is adaptively changed to incorporate information about the results of the search process and transfer this 'knowledge' to the population.

Online publication date: Mon, 30-Nov-2009

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