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- W2017681665 abstract "Purpose – The purpose of this paper is to present a new multi‐objective clonal selection algorithm (MCSA) for the solution of electromagnetic optimization problems.Design/methodology/approach – The method performs the somatic hypermutation step using different probability distributions, balancing the local search in the algorithm. Furthermore, it includes a receptor editing operator that implicitly realizes a dynamic search over the landscape.Findings – In order to illustrate the efficiency of MCSA, its performance is compared with the nondominated sorting genetic algorithm II (NSGA‐II) in some analytical problems and in the well‐known TEAM benchmark Problem 22. Three performance evaluation techniques are used in the comparison, and the effect of each operator of the MCSA in its accomplishment is estimated.Research limitations/implications – In the analytical problems, the MCSA enhanced both the extension and uniformity in its solutions, providing better Pareto‐optimal sets than the NSGA‐II. In the Proble..." @default.
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- W2017681665 date "2009-07-10" @default.
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- W2017681665 title "New operators for multi‐objective clonal selection algorithms" @default.
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- W2017681665 doi "https://doi.org/10.1108/03321640910958955" @default.
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