摘要
针对柔性制造单元的员工交叉培训规划问题,从人性化和经济效益的角度考虑,提出了将多能工水平和任务覆盖水平等培训策略作为约束条件,以培训员工平均满意度最大化和任务平均支付工资最小化为目标的多目标优化方法.针对多目标优化模型,采用了非支配排序遗传算法(NSGA-Ⅱ)求解,并采用了Pareto解集过滤器技术.实验结果表明,改进的算法在一定程度上提高了运算效率和改善了Pareto解的多样性.
To solve the problems of a cross-training plan for staffs in a flexible assembly cell from the point of views of humanization and economy,a multi-objective optimal cross-training plan is proposed.Average labor satisfaction and average task payment are chosen as the goals of the model,and the multi-functionality and task coverage policies are used as the constraints.To solve the multi-objective optimal model,the non-dominated sorting genetic algorithm-II based on double terminated rules and Pareto filter techniques is proposed.Simulation results show that this algorithm improves the operation efficiency and diversity of the Pareto solutions.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第12期1696-1699,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(70971019)
国家创新研究群体科学基金资助项目(71021061)
中央高校基本科研业务费专项资金资助项目(N100404026)
关键词
交叉培训
单元装配线
员工满意度
多目标优化
非支配排序遗传算法
cross-training
assembly cell
labor satisfaction
multi-objective optimization
non-dominated sorting genetic algorithm
