基于Tabu搜索与遗传算法研究拆卸序列优化

Optimization of disassembly sequence based on Tabu search and genetic algorithms

针对废弃装配体的拆卸序列优化,提出建立描述装配体结构的干涉自由矩阵以及“拆卸楔”的概念和算法,据此计算各个零件从装配体上可以拆卸下来的方向和次序.鉴于遗传计算过程中,其邻域往往过早地收敛于局部优化点上,于是将Tabu搜索组合到遗传算法之中.实例验证表明,用这种组合优化方法解决装配体拆卸序列优化问题,所生成的可行拆卸序列在适应度函数值、数量、分布范围等方面均优于单纯的由遗传算法生成的结果.

The aim of the study was to optimize disassembly sequences about worn-out or malfunctioning products. Firstly, it was proposed to build an interference-freeness matrix to describe the structure of assembly, and new ideas about and algorithm for disassembly wedge were proposed, Then, the order for each part to be disassembled from assembly was determined. In consideration of the fact that the neighborhood may converge too fast and limit the search to a local optimum prematurely during the process of genetic algorithms （GAs）, a detailed flow chart of the hybrid approach was presented by combination of Tabu search with GAs. Case study shows that the valid disassembly sequences obtained by the present method are superior to those derived by GAs alone in fitness value, number, and range.