Open Access

ARTICLE

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

Lianqiang Wu, Deming Lei^*, Yutong Cai

School of Automation, Wuhan University of Technology, Wuhan, 430070, China

* Corresponding Author: Deming Lei. Email:

(This article belongs to the Special Issue: Algorithms for Planning and Scheduling Problems)

Computers, Materials & Continua 2025, 83(2), 1771-1789. https://doi.org/10.32604/cmc.2025.063944

Received 29 January 2025; Accepted 10 March 2025; Issue published 16 April 2025

Abstract

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 those with high evolutionary potential are retained to continue their evolution. To evaluate 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.

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Keywords

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