In this paper, a new fuzzy logic based decision support system for parallel machine scheduling/rescheduling in the presence of uncertain disruptions is presented. It is applied to a real-life problem identified in a pottery company. The uncertain disruption considered is glaze shortage, defined by two parameters: number of glaze shortage occurrences and glaze shortage duration. Both parameters are specified imprecisely. They are modelled and combined using standard fuzzy sets and level 2 fuzzy sets, respectively. In order to deal with the glaze shortage disruption, a predictive–reactive scheduling approach is proposed and implemented. It is defined as a two-step procedure. In the first step, a predictive schedule is generated in such a way as to being capable of absorbing the impact of the glaze shortage disruption. In the second step, rescheduling is applied when the impact of the glaze shortage disruption is too high. Two sets of Sugeno type rules are proposed to support rescheduling decision making. One set of the fuzzy rules determines when to reschedule, whilst the other one determines which rescheduling method to use. Various tests are carried out that show that (1) the predictive schedules have good performance in the presence of uncertain disruptions and (2) the fuzzy inference generates appropriate rescheduling decisions.
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- Fuzzy inference systems
- Level 2 fuzzy sets
- Predictive scheduling
- Genetic algorithms