A differential evolution variant of nsga ii for real world multiobjective optimization
C Kwan, F Yang, C Chang - Progress in Artificial Life: Third Australian …, 2007 - Springer
C Kwan, F Yang, C Chang
Progress in Artificial Life: Third Australian Conference; ACAL 2007 Gold Coast …, 2007•SpringerThis 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 …
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 …
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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