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首页> 外文期刊>Journal of Intelligent Manufacturing >Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining
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Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

机译：使用混合遗传算法和智能搜索进行车间加工的优化工艺计划

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摘要

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.
机译：流程计划的优化被认为是计算机辅助流程计划的关键技术，这是一个相当复杂且困难的过程。一个良好的零件工艺计划是建立在两个要素的基础上的：（1）零件操作的最佳顺序； （2）针对每个操作优化选择机器，切削刀具和工具访问方向（TAD）。在当前工作中，过程计划分为初步计划和次要/详细计划。在初始阶段，基于顺序和聚类约束的分析，作为操作排序中的强制性约束聚合，并使用智能搜索策略，生成可行序列。然后，在详细的计划阶段，使用修剪初始可行序列的遗传算法，获得基于优化约束作为加性约束集合的，优化的操作序列以及每次操作的机器，切削刀具和TAD的优化选择。这项工作的主要贡献是使用智能搜索和遗传算法同时优化零件操作的顺序，并优化每次操作的机器选择，切削工具和TAD。

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