Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

中文翻译：

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使用混合遗传算法和智能搜索优化工艺规划，用于作业车间加工。

工艺规划的优化被认为是计算机辅助工艺规划的关键技术，这是一个相当复杂和困难的过程。一个好的零件工艺计划是基于两个要素建立的：（1）零件操作的优化顺序；(2) 为每个操作优化选择机器、刀具和刀具访问方向 (TAD)。在目前的工作中，工艺规划分为初步规划和二次/详细规划。在初步阶段，基于对作为操作排序中的强制约束聚合的顺序和聚类约束进行分析，并采用智能搜索策略，生成可行序列。然后，在详细规划阶段，使用遗传算法对初始可行序列进行剪枝，以优化约束为加性约束聚合，得到优化的操作顺序和每次操作的机床、刀具和TAD的优化选择。这项工作的主要贡献是优化零件的操作顺序，同时使用智能搜索和遗传算法优化每个操作的机器选择、刀具和TAD。