面向服务的网络化协同制造资源多目标重组优化调度  

Multi-objective Reconfiguration and Optimal Scheduling of Service-oriented Networked Collaborative Manufacturing Resource

作　　者：韦韫[1] 李东波[1] 童一飞[1] 

机构地区：[1]南京理工大学机械工程学院,南京210094

出　　处：《农业机械学报》2012年第3期193-199,共7页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金资助项目(61104171)

摘　　要：针对网络化协同制造资源重组优化调度所存在的问题,综合考虑影响网络化协同制造资源重组优化调度的4个主要因素:最小化生产作业时间、最小化生产作业成本、最优化生产加工质量、最优化资源服务质量,建立了网络化协同制造资源多目标优化调度的数学模型。提出了一种基于Pareto多目标免疫遗传算法的网络化协同制造资源重组优化调度方法,该算法综合运用了小生境技术、群体排序技术和精英保留策略,并对遗传算子进行改进,自适应地调整交叉和变异算子,结合免疫算法的免疫选择淘汰了相似个体,保证了种群多样性,避免了早熟现象的发生。免疫记忆对近似最优解进行动态邻域搜索,提高了算法的局部搜索能力。实例仿真表明了该算法的有效性。In order to solve reconfiguration and optimal scheduling problems of networked collaborative manufacturing resource,a multi-objective optimization mathematical model was provided with four practical important objectives were considered simultaneously,including minimizing the total production working hours,total production working cost,optimization total production processing quality and resource service quality.A reconfiguration and optimal scheduling method for networked collaborative manufacturing resource was presented based on Pareto multi-objective immune genetic algorithm.In order to ensure the groups variety,prevent the premature convergence problem,some key technologies such as population ranking technique,niche technique,Pareto solution set filter were applied.The genetic operators were improved and self-adaptive crossover and mutation operators were proposed by the algorithm,and immune selection could eliminate semblable individuals.Immune memory was adopted to dynamic search near each approximate optimal solution,so it accelerated search and improved quality of solution.Finally the result of simulation indicated the validity of algorithm.

关 键 词：网络化协同制造 多目标优化 调度 免疫遗传算法 

分 类 号：F407.67[经济管理—产业经济]