Abstract
Green manufacturing has attracted increasing attention under the background of carbon peaking and carbon neutrality. Distributed production has widely existed in various manufacturing industries with the development of globalization. This paper investigates an energy-efficient distributed no-wait flow-shop scheduling problem with sequence-dependent setup time (DNWFSP-SDST) to minimization of makespan and total energy consumption (TEC). A mixed-integer linear programming model of energy-efficient DNWFSP-SDST is constructed and a cooperative meta-heuristic algorithm based on Q-learning (CMAQ) is proposed to address energy-efficient DNWFSP-SDST in this paper. In CMAQ, a heuristic named RNRa is proposed to generate initial solutions. A bi-population cooperative framework based on double Q-learning is designed to further optimize the solutions. According to the properties of energy-efficient DNWFSP-SDST, an energy-saving strategy based on knowledge is proposed to improve makespan and TEC. The results of experiments show that the performance of CMAQ is superior to certain state-of-the-art comparison algorithms in solving energy-efficient DNWFSP-SDST.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
