This paper addresses a bi-objective distribution permutation flow shop scheduling problem (FSP) with setup times aiming to minimize the makespan and the total tardiness. It is very difficult to obtain an optimal solution by using traditional approaches in reasonable computational time. This paper presents an appropriate non-dominated sorting Genetic Algorithm III based on the reference point. The NEH strategy is applied into the generation of the initial solution set. To validate the performance of the NEH strategy improved NSGA III (NNSGA III) on solution quality and diversity level, various test problems are carried out. Three algorithms, including NSGA II, NEH strategy improved NSGA II(NNSGA II) and NNSGA III are utilized to solve this FSP. Experimental results suggest that the proposed NNSGA III outperforms the other algorithms on the Inverse Generation Distance metric, and the distribution of Pareto solutions are improved excellently.
Optimizing Bi-Criteria Permutation Flow Shop Scheduling Problem by Improved NSGA III
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Meng, R, Rao, Y, & Luo, Q. "Optimizing Bi-Criteria Permutation Flow Shop Scheduling Problem by Improved NSGA III." Proceedings of the ASME 2018 13th International Manufacturing Science and Engineering Conference. Volume 4: Processes. College Station, Texas, USA. June 18–22, 2018. V004T03A030. ASME. https://doi.org/10.1115/MSEC2018-6493
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