An Adaptive Cooperated Shuffled Frog-Leaping Algorithm for Parallel Batch Processing Machines Scheduling in Fabric Dyeing Processes  

作　　者：Lianqiang Wu Deming Lei Yutong Cai 

机构地区：[1]School of Automation,Wuhan University of Technology,Wuhan,430070,China

出　　处：《Computers, Materials & Continua》2025年第5期1771-1789,共19页计算机、材料和连续体(英文)

摘　　要：Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines(BPM).In this study,the parallel BPM scheduling problem with machine eligibility in fabric dyeing is considered,and an adaptive cooperated shuffled frog-leaping algorithm(ACSFLA)is proposed to minimize makespan and total tardiness simultaneously.ACSFLA determines the search times for each memeplex based on its quality,with more searches in high-quality memeplexes.An adaptive cooperated and diversified search mechanism is applied,dynamically adjusting search strategies for each memeplex based on their dominance relationships and quality.During the cooperated search,ACSFLA uses a segmented and dynamic targeted search approach,while in non-cooperated scenarios,the search focuses on local search around superior solutions to improve efficiency.Furthermore,ACSFLA employs adaptive population division and partial population shuffling strategies.Through these strategies,memeplexes with low evolutionary potential are selected for reconstruction in the next generation,while thosewithhighevolutionarypotential are retained to continue their evolution.Toevaluate the performance of ACSFLA,comparative experiments were conducted using ACSFLA,SFLA,ASFLA,MOABC,and NSGA-CC in 90 instances.The computational results reveal that ACSFLA outperforms the other algorithms in 78 of the 90 test cases,highlighting its advantages in solving the parallel BPM scheduling problem with machine eligibility.

关 键 词：Batch processing machine parallel machine scheduling shuffled frog-leaping algorithm fabric dyeing process machine eligibility 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]