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IEEE Intelligent Systems
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Design of multi-objective evolutionary algorithms: application to the flow-shop scheduling problem
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Genetic algorithms, path relinking, and the flowshop sequencing problem
Evolutionary Computation
Parallel Path-Relinking Method for the Flow Shop Scheduling Problem
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Experimental genetic operators analysis for the multi-objective permutation flowshop
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
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This paper presents and investigates different ways to integrate path relinking techniques into the hypervolume-based multi-objective local search algorithm (HBMOLS). We aim to evaluate the effectiveness of different path relinking strategies, these strategies focus on two main steps: the ways of path generation and the mechanisms of solutions selection. We propose different methods to establish the path relinking algorithms in a multi-objective context. Computational results on a bi-objective flow shop problem (FSP) and a statistical comparison are reported in the paper. In comparison with two versions of HBMOLS, the algorithms selecting a set of solutions located in the middle of the generated path are efficient. The behavior of these algorithms sheds light on ways to further improvements.