求解双资源约束车间调度问题的继承式双目标遗传算法  

Double-objective inherited genetic algorithm for dual resource constrained job shop

作　　者：李兢尧[1] 孙树栋[1] 黄媛[1] 牛刚刚[1] 

机构地区：[1]西北工业大学系统集成与工程管理研究所现代设计与集成制造教育部重点实验室,西安710072

出　　处：《控制与决策》2011年第12期1761-1767,1776,共8页Control and Decision

基　　金：国家863/CIMS计划项目(2007AA042187);国家自然科学基金项目(50705076,50705077)

摘　　要：针对双资源约束作业车间调度的双目标优化问题,提出一种继承式遗传算法,通过分支种群继承父辈种群的进化经验.该算法面向双资源约束特点,采用4维染色体编码方式,基于时间窗口比较实现活动化调度,通过资源进化算子提高算法全局搜索能力;基于个体Pareto指数的锦标赛选择策略,有效削弱了染色体Pareto排序级别对个体存活概率的影响以保持群体多样性,并利用精英保留策略提高了解的收敛性.仿真实验与分析结果表明了所提算法具有优良性能.To solve the double-objective optimal of dual resource constrained job shop scheduling problem, an inherited genetic algorithm is proposed, in which the evolutionary experience of parent population is inherited by the means of branch population generation with pheromones to accelerate the convergence rate. Meanwhile, by using the four-dimensional chromosome coding method, based on comparison among time windows, the activable decoding algorithm is utilized with reference to the Character of dual resource constrained to improve the overall searching ability. During the evolution process, the championship selection strategy based on Pareto index weakens the impact of the Pareto level of chromosomes obviously to keep the community diversity. The reliable convergence of algorithm is guaranteed by using elitist preservation strategy. The simulation experiment and statistical analysis on extant and random example show that the proposed method has good performance.

关 键 词：双资源约束 继承式遗传算法 时间窗口比较 Pareto指数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]