A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling

• URL: http://arxiv.org/abs/2004.06564v1
• Date: Tue, 14 Apr 2020 14:49:36 GMT
• Title: A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling
• Authors: Yali Wang, Bas van Stein, Michael T.M. Emmerich, Thomas B\"ack
• Abstract summary: A customized evolutionary algorithm is proposed to solve the flexible job scheduling problem. Different local search strategies are employed to explore the neighborhood parameters for better solutions. The experimental results show excellent performance with less computing budget.
• Score: 18.401817124823832
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A customized multi-objective evolutionary algorithm (MOEA) is proposed for the multi-objective flexible job shop scheduling problem (FJSP). It uses smart initialization approaches to enrich the first generated population, and proposes various crossover operators to create a better diversity of offspring. Especially, the MIP-EGO configurator, which can tune algorithm parameters, is adopted to automatically tune operator probabilities. Furthermore, different local search strategies are employed to explore the neighborhood for better solutions. In general, the algorithm enhancement strategy can be integrated with any standard EMO algorithm. In this paper, it has been combined with NSGA-III to solve benchmark multi-objective FJSPs, whereas an off-the-shelf implementation of NSGA-III is not capable of solving the FJSP. The experimental results show excellent performance with less computing budget.

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