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A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. (English) Zbl 1144.90393
Summary: A discrete particle swarm optimization (DPSO) algorithm is presented to solve the no-wait flowshop scheduling problem with both makespan and total flowtime criteria. The main contribution of this study is due to the fact that particles are represented as discrete job permutations and a new position update method is developed based on the discrete domain. In addition, the DPSO algorithm is hybridized with the variable neighborhood descent (VND) algorithm to further improve the solution quality. Several speed-up methods are proposed for both the swap and insert neighborhood structures. The DPSO algorithm is applied to both 110 benchmark instances of E. Taillard [Eur. J. Oper. Res. 64, No. 2, 278–285 (1993; Zbl 0769.90052)] by treating them as the no-wait flowshop problem instances with the total flowtime criterion, and to 31 benchmark instances provided by J. Carlier [RAIRO, Rech. Opér. 12, 333–350 (1978; Zbl 0401.90052)], J. Heller [Oper. Res. 8, 178–184 (1960; Zbl 0092.27910)], and C. R. Reeves [Comput. Oper. Res. 22, No. 1, 5–13 (1995; Zbl 0815.90097)] for the makespan criterion. For the makespan criterion, the solution quality is evaluated according to the reference makespans generated by Ch. Rajendran [J. Oper. Res. Soc. 45, No. 4, 472–478 (1994; bl 0799.90060)] whereas for the total flowtime criterion, it is evaluated with the optimal solutions, lower bounds and best known solutions provided by A. Fink and St. Voß [Eur. J. Oper. Res. 151, No. 2, 400–414 (2003; Zbl 1052.90030)]. The computational results show that the DPSO algorithm generated either competitive or better results than those reported in the literature. Ultimately, 74 out of 80 best known solutions provided by Fink and Voß [loc. cit.] were improved by the VND version of the DPSO algorithm.
90B35Scheduling theory, deterministic
90C59Approximation methods and heuristics
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