Abstract
This paper proposes the replacement of mutation and crossover operators of the NSGA II with a variant of differential evolution (DE). The resulting algorithm, termed NSGAII-DE, is tested on three test problems, and shown to be comparable to NSGA II. The algorithm is subsequently applied to two real world problems: (i.) a mass rapid transit scheduling problem and (ii.) the optimization of inspection frequencies for power substations. For both the real world problems, NSGAII-DE is found to have generated better results based on comparative studies.
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Kwan, C., Yang, F., Chang, C. (2007). A Differential Evolution Variant of NSGA II for Real World Multiobjective Optimization. In: Randall, M., Abbass, H.A., Wiles, J. (eds) Progress in Artificial Life. ACAL 2007. Lecture Notes in Computer Science(), vol 4828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76931-6_30
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DOI: https://doi.org/10.1007/978-3-540-76931-6_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76930-9
Online ISBN: 978-3-540-76931-6
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