Abstract

The presence of setup times and multiple objectives makes the scheduling problem complex. This paper presents two algorithms namely: multi-objective simulated annealing (MOSA) and modified MOSA for the simultaneous minimisation of makespan and mean tardiness in scheduling a flow shop production system wherein setup times depend on processing sequence. The modified MOSA algorithm is developed by hybridising MOSA with variable neighbourhood search. Benchmark problems are used to conduct computational experiments. The analysis of the algorithms reveals that modified MOSA outperforms MOSA for the measures considered. Hybridisation improves the performance of MOSA. The proposed algorithms are applied on scheduling a real-world SDST flow shop and the results indicate superior performance of modified MOSA.

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