摘要
双边装配线应用广泛,翻转工位操作能有效降低部分零件装配难度与操作风险,但增加了设计难度。基于此,研究了附带翻转工位操作的挖掘机底盘双边装配线规划设计问题,针对该问题提出了一种改进蚁群算法求解。给出了问题求解的启发式任务分配规则,提出可采用启发式任务选择规则以提高算法收敛速率。进而分析某型挖掘机底盘装配线得出先后约束关系图,将问题抽象为双边装配线优化设计问题。随后,采用两种蚁群算法进行附带翻转工位的装配线优化,分析比较了两种算法因结构差异对优化结果所造成的影响。
An improved ant colony optimization is proposed for solving the two sided excavator chassis’s assembly lines with station flipping tasks. The flipping task can decrease the assembly difficulty and operational risk but will greatly in-crease the planning and design difficulty. A heuristic task assignment method is presented for solving distributing the station flipping tasks. The heuristic task selection method is used to accelerate to find a feasible solution. The tasks’priority diagram is proposed after studying the assembly relationship between the tasks and the problem is abstracted into two sided assembly line balancing problem. The standard and improved ant colony algorithms are used for contradistinction on solving this problem. And this paper studies the inference brought by the inner structure of this two algorithms.
出处
《计算机工程与应用》
CSCD
2014年第6期240-245,共6页
Computer Engineering and Applications
基金
国家自然科学基金(No.51205328)
高等学校博士学科点专项科研基金资助课题(No.200806131014)
教育部人文社会科学研究青年基金项目(No.12YJCZH296)
中央高校基本科研业务费专项资金资助项目(No.SWJTU09CX022)
关键词
蚁群算法
双边装配线
翻转工位
优化
群智能
Ant Colony Optimization(ACO)
two-sided assembly lines
station flipping task
optimization
swarm intelligence