A Customer-Oriented Method to Support Multi-Tasks Scheduling Under Uncertain Time in Cloud Manufacturing

Cloud Manufacturing is customer-oriented manufacturing under uncertain environments, and it is significant to enhance customers satisfaction. However, previous studies had not paid enough attention to the nonrational customer under uncertain environments, and we design customer-oriented fuzzy scheduling based on the cloud model. First, previous studies had mainly studied deterministic scheduling, but fuzzy scheduling had not attracted enough attention. Because of the uncertain environment, we study fuzzy scheduling in Cloud Manufacturing. Second, for fuzzy scheduling, the previous uncertain forms had difficulty presenting the distributed features of collected data, we use the cloud model to perform the uncertain data. Third, previous studies proposed that satisfaction was linear with the index value, such as tardiness or earliness, but nonrational customers were not considered. We use prospect theory to calculate the satisfaction of nonrational customers. Finally, to solve the scheduling problem, we design an enhanced gray wolf optimization with a parallel searching mechanism. The advantages of our algorithm are verified by comparison with other similar algorithms.