遗传算法求解低碳柔性车间生产调度问题  

Genetic Algorithm for Solving Flexible Job Shop Scheduling Problem with Low Carbon

作　　者：张国辉[1] 党世杰[1] 

机构地区：[1]郑州航空工业管理学院管理工程学院,郑州450015

出　　处：《组合机床与自动化加工技术》2016年第11期141-144,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金(61203179);河南省高校科技创新人才支持计划资助(14HASTIT006);河南省高等学校青年骨干教师资助计划(2014GGJS-105);航空科学基金(2014ZG55016);郑州航院研究生教育创新计划基金(2015CX009);河南省软科学项目(JYB2013034)

摘　　要：低碳生产方式已成为当前各国所认可的生产方式,是可持续发展的必然要求。从满足最大完工时间最小和生产碳排放量最小角度出发,构建低碳车间调度模型。使用改进的遗传算法对有低碳需求的车间生产方式进行求解,在求解过程中对初始解生成机制和遗传算子进行改进,提高算法收敛速度。实验结果证明提出的改进遗传算法在求解车间低碳生产调度中是可行的。Low carbon production mode has become the current accepted production mode, it is also the in-evitable requirement of sustainable development. Low carbon flexible job shop scheduling model is built to meet the target of minimum makespan and producing carbon emissions. An improved genetic algorithm is proposed to solve the workshop production mode with low carbon requirements, in the process of solving, the initial solution and genetic operator are improved to enhance the algorithm convergence speed. Finally, the experimental results show that the proposed improved genetic algorithm is feasible in solving low carbon production scheduling.

关 键 词：低碳 遗传算法 柔性作业车间调度 优化 

分 类 号：TH16[机械工程—机械制造及自动化] TG506[金属学及工艺—金属切削加工及机床]