A comparison of algorithms for minimizing the sum of earliness and tardiness in hybrid flow-shop scheduling problem (Unrelated parallel machines and sequence-dependent setup times)

In this paper, we consider the flow-shop scheduling problem with unrelated parallel machines at each stage as well as sequence-dependent setup times under minimization of the sum of earliness and tardiness. Processing times, setup times and due-dates are known in advance. To solve the problem, we introduce a hybrid memetic algorithm and a particle swarm optimization combined with genetic operators. An application of simulated annealing is also presented for the evaluation of the proposed algorithm. A Taguchi design is also conducted to set the parameters. Finally, a comparison is made via 16 small size and 24 large size test problems for 10 times each. The results of one-way ANOVA applied in our test problems, demonstrate that the proposed algorithm performs as efficient as the HSA qualitatively and with 63.77% decline in elapsed time.