Affiliations: Department of Industrial Engineering, University of Kurdistan, Pasdaran Boulevard, Sanandaj, Iran
Correspondence:
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Corresponding author. Fardin Ahmadizar, Department of Industrial Engineering, University of Kurdistan, Pasdaran Boulevard, Sanandaj, Iran. E-mail: [email protected].
Abstract: The group shop scheduling (GSS) problem is a general formulation that includes the job shop and the open shop scheduling problems. This paper is the first dealing with a GSS problem with random release and processing times and fuzzy due dates. While release and processing times are assumed to be random variables with known distributions, as in many real-world situations, job due dates are considered to be fuzzy tolerating a certain amount of delay. The objective is to maximize the expected total degree of satisfaction with respect to the fuzzy due dates. The problem is formulated as a stochastic disjunctive program and then two solution approaches are developed for it, both of which act within an ant colony optimization (ACO) framework. In the first approach, to estimate the performance of a constructed schedule, each random variable is replaced by its expectation, whereas in the other approach following a simulation optimization procedure, a discrete event simulation model is employed to estimate the performance of a schedule. The proposed approaches are then compared through computational experiments.
Keywords: Group shop scheduling, random release times, random processing times, fuzzy due dates, ant colony optimization, simulation
