湖北汽车工业学院学报2026，Vol.40Issue(2)：65-70,6.DOI:10.3969/j.issn.1008-5483.2026.02.012
基于多策略融合遗传算法的柔性作业车间双目标调度优化
Bi-objective Optimization of Flexible Job Shop Scheduling Using Genetic Algorithm Integrating Multiple Strategies
摘要
Abstract
For the flexible job shop scheduling problem,a mathematical model was formulated with the optimization objectives of minimizing makespan and carbon emissions.An enhanced genetic algorithm integrating multiple strategies was proposed.A chaos-based initialization method was employed to gen-erate a high-quality population,while adaptive crossover and mutation probabilities were introduced to accelerate convergence.A Lévy flight strategy was incorporated to strengthen the global search capabili-ty,and a simulated annealing algorithm with an improved cooling curve was hybridized to enhance local search ability.Case studies and examples for verification demonstrate that compared with other algo-rithms,the proposed method not only exhibits significant advantages in reducing makespan but also achieves promising results in carbon emission optimization.关键词
遗传算法/完工时间/碳排放/柔性车间调度Key words
genetic algorithm/makespan/carbon emission/flexible job shop scheduling分类
机械制造引用本文复制引用
钱航,李峰,周学良..基于多策略融合遗传算法的柔性作业车间双目标调度优化[J].湖北汽车工业学院学报,2026,40(2):65-70,6.基金项目
国家自然科学基金(52075107) （52075107）
湖北省高等学校优秀中青年科技创新团队计划项目(T2020018) （T2020018）
智能输送技术与装备湖北省重点实验室开放课题(2025XM102) （2025XM102）
