A mapping technique for better solution exploration: NSGA-II adaptation

Julien Autuori (), Faicel Hnaien () and Farouk Yalaoui ()
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Julien Autuori: Université de Technologie de Troyes
Faicel Hnaien: Université de Technologie de Troyes
Farouk Yalaoui: Université de Technologie de Troyes

Journal of Heuristics, 2016, vol. 22, issue 1, No 3, 89-123

Abstract: Abstract A mapping method (MaM) for a better solution space exploration adapted to NSGA-II method is presented. The Mapping technique divides the solution space into several zones using a Hamming distance to a reference solution. We present a bijective mapping function from the search space to the binary representation space of solutions. For each zone, a mapping metric is used to evaluate the solution space exploration. According to this evaluation, a local search is performed. The mapping is adapted to the well known non-dominated sorting genetic algorithm-II (NSGA-II) method applied to solve the flexible job shop problem (FJSP) case. We present the comparison between the hybridization using the local search for the non-dominated solutions and the hybridization using the mapping metrics. The multi-objective metrics show the efficiency of mapping adaptation in terms of convergence and diversity.

Keywords: Multi-objective; Flexible job shop problem; NSGA-II; Solution space exploration; Mapping technique (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10732-015-9303-4

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