基于遗传算法的加工方案选择与操作排序综合优化方法

A GA-Based Synthesizing Optimization Approach for Machining Scheme Selection and Operations Sequencing

为了得到全局最优工艺计划,提出一种基于遗传算法的可行加工方案选择与操作排序综合优化方法.考虑了特征有多个可行加工方案且其选择概率不同,在每次外层迭代中,由轮盘赌算法选择其一用于操作排序优化.通过内层的遗传算法获取子最优工艺计划,在外层比较各子最优工艺计划来获取全局最优工艺计划.特征的操作优先约束随着加工方案选择的不同而自动改变,并用于约束调整算法来保证解的可行性.实例验证了该方法的有效性,并发现了全局最优工艺计划产生于选择各特征的最大选择概率对应的可行加工方案的规律.

To get the global optimal process plan, a synthesizing optimization approach for machining scheme selection and operations sequencing based on genetic algorithm （GA） was proposed. In the outer iteration, considering that each feature might have alternative machining schemes and their selection probabilities are different, the roulette algorithm is used to select one of them for operations sequencing optimization. By the inner GA, the sub-optimal process plan is generated. Through comparing the sub-optimal process plans, the global optimal process plan can be obtained. The operations precedence constraints of features can be changed automatically with the selection of different machining schemes, and be used in constraint adjustment algorithm to ensure the solutions＇ feasibility. Finally, the validity of the approach was demonstrated by case study, and the rule that the global optimal process plan is generated by selecting the available machining scheme with the highest selection probability for each feature was found.