基于差分遗传算法的置换流水车间低碳调度模型  

Low-carbon scheduling in permutation flow shop problem by differential genetic algorithm

作　　者：杨海东[1] 郑庆仁 刘国胜[3] 郭建华[4] 

机构地区：[1]广东工业大学机电工程学院,广东广州510006 [2]华南理工大学自动化科学与工程学院,广东广州510641 [3]广东工业大学信息管理工程系,广东广州510520 [4]广东技术师范学院计算机科学学院,广东广州510665

出　　处：《中南大学学报（自然科学版）》2013年第11期4554-4560,共7页Journal of Central South University:Science and Technology

基　　金：国家科技支撑计划项目(2012BAF12B10);教育部人文社科青年项目(12YJCZH129);广东省教育部产学研结合项目(2011A090200050);广东省重大科技专项(2012A080104022);广东省科技计划项目(2011B01070052;2012B010500027;2012B010900064)

摘　　要：研究置换流水车间(permutation flow shop,PFS)中的能效优化问题,考虑串行生产线中机器功率、空闲时间等因素对能源消耗的影响,建立以高效低碳为目标的PFS模型。给出问题的数学规划形式,并采用遗传算法对其求解,所给出的遗传算法通过启发式规则、随机规则和翻转规则产生初始种群,根据任务的能耗差分来计算种群中个体的进化概率和进化方向,同时提出非等长LOX交叉算子。对华南地区某大型轮胎制造企业进行实例分析,研究结果表明:所采用的改进策略可提高遗传算法整体性能50%以上;采用文中模型和方法可降低轮胎生产过程能耗8%左右。The energy-efficient optimization in permutation flow shop （PFS） was investigated. A novel high-efficiency low-carbon model was proposed in which effects of machine power consumption and idle time were considered on energy consumption. The problem was formulated by mathematical programming and solved by genetic algorithm （GA）. Adopting heuristic rule, random rule, and reverse rule to generate the initial population, and determining the evolution direction and probability according to the difference of energy consumption, an unequal LOX crossover operation was also adopted. A case study for a tire manufacturing company located in South China was made. The results show that the proposed scheme improves the performance of GA at least 50%. The proposed method can reduce approximately 8% energy consumption in tire manufacturing process.

关 键 词：置换流水车间 能效优化 遗传算法 差分策略 轮胎生产 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]