Jing Wang , Deming Lei , Debiao Li , Xixing Li , Hongtao Tang
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引用次数: 0
Abstract
Distributed energy-efficient hybrid flow shop scheduling problem (DEHFSP) with batch processing machines (BPMs) is rarely considered, let alone DEHFSP with BPMs and uncertainty. In this study, a fuzzy DEHFSP with BPMs at a middle stage and no precedence between some stages is presented, and a dynamic artificial bee colony (DABC) is proposed to simultaneously optimize the total agreement index, fuzzy makespan, and fuzzy total energy consumption. To produce high quality solutions, Metropolis criterion is used, dynamic employed bee phase based on neighborhood structure dynamic selection is implemented, and group-based onlooker bee phase with bidirectional communication is given. Migration operator is also adopted to replace scout bee phase. Extensive experiments are conducted, and the optimal combination of key parameters for DABC is decided by the Taguchi method. Comparative results and statistical analysis show that new strategies of DABC are effective, and DABC is highly competitive in solving the considered fuzzy DEHFSP.
期刊介绍:
The Journal of Manufacturing Systems is dedicated to showcasing cutting-edge fundamental and applied research in manufacturing at the systems level. Encompassing products, equipment, people, information, control, and support functions, manufacturing systems play a pivotal role in the economical and competitive development, production, delivery, and total lifecycle of products, meeting market and societal needs.
With a commitment to publishing archival scholarly literature, the journal strives to advance the state of the art in manufacturing systems and foster innovation in crafting efficient, robust, and sustainable manufacturing systems. The focus extends from equipment-level considerations to the broader scope of the extended enterprise. The Journal welcomes research addressing challenges across various scales, including nano, micro, and macro-scale manufacturing, and spanning diverse sectors such as aerospace, automotive, energy, and medical device manufacturing.