Hybrid Genetic Algorithms for the Single Machine Scheduling Problem with Sequence-Dependent Setup Times

Several researches on scheduling problems have been done under the assumption that setup times are independent of job sequence. However, in certain contexts, such as the pharmaceutical industry, metallurgical production, electronics and automotive manufacturing, there are frequently setup times on equipment between two different activities. In a survey of industrial schedulers, Dudek et al. (1974) reported that 70% of industrial activities include sequence-dependent setup times. More recently, Conner (2009) has pointed out, in 250 industrial projects, that 50% of these projects contain sequence-dependent setup times, and when these setup times are well applied, 92% of the order deadline could be met. Production of good schedules often relies on management of these setup times (Allahverdi et al., 2008). This present chapter considers the single machine scheduling problem with sequence dependent setup times with the objective to minimize total tardiness of the jobs (SMSDST). This problem, noted as 1|sij|ΣTj in accordance with the notation of Graham et al. (1979), is an NP-hard problem (Du & Leung, 1990).

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