纺织工程学报2025，Vol.3Issue(5)：63-72,10.
面向绿色纺织柔性作业车间调度的混沌协同进化算法
Chaotic co-evolutionary algorithm for green textile flexible job-shop scheduling
摘要
Abstract
To address the green scheduling requirements in flexible production workshops of the textile industry,a Chaotic Synergistic Evolutionary Algorithm(CSEA)integrating discrete particle swarm optimization with sim-ulated annealing mechanisms was developed to optimize production efficiency and equipment energy consump-tion.Firstyl,a multi-objective scheduling model incorporating textile equipment energy consumption was estab-lished using a classical genetic algorithm framework,with innovative implementation of a chaos theory-based dynamic crossover probability adjustment mechanism.Logistic mapping equations were employed to enhance diversity search capability during scheduling processes.Then,discrete particle swarm optimization was embed-ded in population evolution to optimize textile equipment load distribution,complemented by simulated anneal-ing for refined neighborhood search of processes,achieving dual optimization of global exploration and local ex-ploitation.Finally,by using an adaptive early stopping strategy to terminate invalid iterations dynamically,the time cost is significantly reduced.After testing on the Kacem dataset,compared with traditional genetic algo-rithms and standard particle swarm optimization algorithms,the proposed hybrid algorithm has improved con-vergence speed by 37.6%,effectively tackling the textile equipment scheduling and energy consumption control challenges in multi-variety,small-batch production scenarios.关键词
柔性作业车间调度/混沌协同进化算法/离散粒子群优化/模拟退火/邻域搜索Key words
flexible job-shop scheduling/hybrid genetic algorithm/discrete particle swarm optimization/simu-lated annealing/neighborhood search分类
轻工纺织引用本文复制引用
唐家琦,秦冠兴,王鑫涛,张紫情,杜利珍..面向绿色纺织柔性作业车间调度的混沌协同进化算法[J].纺织工程学报,2025,3(5):63-72,10.基金项目
湖北省数字化纺织装备重点实验室(DTL2023016). （DTL2023016）
