Scheduling flexible flow lines with sequence-dependent setup times

Abstract

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The hybrid flow shop scheduling problem

“…The same problem, with the addition of sequence dependent setup times was approached in [105] using a GA with the Random Keys representation proposed in [18]. The proposed RKGA outperformed several other specialized heuristics including those of [104].…”

“…Artificial Immune Systems (AIS), for instance, have been used in [47] and in [232]. In the later case, the proposed AIS outperformed the GA proposed in [105]. Neural Networks were used in [65] as a mechanism to decide among several heuristics, for the one to be used on a particular instance.…”

Algorithms for a realistic variant of flowshop scheduling

“…They investigate three classes of heuristics based on simple greedy methods, insertion heuristics and adaptations of the Johnson's rule. Later, Kurz and Askin (2004) formulate the SDST/HFFS as an integer programming (IP) model. Because of the difficulty in solving the IP model directly, they develop a random keys genetic algorithm (RKGA).…”

“…Problem data is generated to compare the RKGA against other heuristic rules. Zandieh, Ghomi and Husseini (2006) proposed an immune algorithm, and compared it favorably against the RKGA of Kurz and Askin (2004).…”

“…In any case, it is unlikely that any such approaches will be able to solve large instances, given the abundant literature on exact methods for simpler problems with setup times and the limited results obtained so far. However, some heuristics and metaheuristics have been proposed for this problem like random keys genetic algorithms and heuristics, Kurz and Askin (2003), Kurz and Askin (2004), genetic algorithms , and artificial immune systems Zandieh, Ghomi and Husseini (2006). In this paper we exploit the flexible and setup time characteristics of the SDST/HFFS in order to obtain competitive results.…”