Abstract
This paper presents a multi-objective differential evolution algorithm (MODE) and its application for solving multi-objective job shop scheduling problems. Five mutation strategies with different search behaviors proposed in the MODE are used to search for the Pareto front. The performances of the MODE are evaluated on a set of benchmark problems and the numerical experiments show that the MODE is a highly competitive approach which is capable of providing a set of diverse and high-quality non-dominated solutions compared to those obtained from existing algorithms.
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© 2013 Springer Science+Business Media Singapore
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Wisittipanich, W., Kachitvichyanukul, V. (2013). A Pareto-Based Differential Evolution Algorithm for Multi-Objective Job Shop Scheduling Problems. In: Lin, YK., Tsao, YC., Lin, SW. (eds) Proceedings of the Institute of Industrial Engineers Asian Conference 2013. Springer, Singapore. https://doi.org/10.1007/978-981-4451-98-7_133
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DOI: https://doi.org/10.1007/978-981-4451-98-7_133
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