A customer-oriented method to support multi-task green scheduling with diverse time-of-use prices in Cloud Manufacturing

Abstract

Green manufacturing has become a hot topic globally, and Cloud Manufacturing (CMfg) provides a novel approach to support green manufacturing through manufacturing services (MS) composition. In this study, we design a customer-oriented method for supporting multi-task green scheduling in CMfg. First, we aim to minimize the total energy consumption during scheduling. Second, because CMfg is a type of customer-oriented manufacturing, the just-in-time objective is used to meet the customers on-time requirements. Subsequently, we study the different time-of-use prices of MS in CMfg. The price of utilizing MS is related not only to cost but also to the supply-demand relationship, which results in diverse time-of-use prices for MS. After establishing the scheduling model, a hybrid artificial bee colony algorithm is designed to solve the scheduling model. For the algorithm, we design a guiding mechanism to enhance the global search ability and an adaptive variable neighborhood search for improving the local search ability. To verify the performance of our algorithm, we compared it with similar algorithms, and the results indicate the high-level performance of our work.