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Machining scheme selection of digital manufacturing based on genetic algorithm and AHP

机译:基于遗传算法和层次分析法的数字制造加工方案选择

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摘要

The selection of machining scheme for a part is an important and strategic problem. It involves multiple and conflicting objectives such as cost, time, quality, service level, resource utilization, etc. The selection is always affected by subjective factors such as the knowledge and experiences of decision maker in conventional machining. This paper proposes a method based on genetic algorithms (GA) to find out the set of Pareto-optimal solutions for multi-objective digital machining scheme selection. To deal with multi-objective and enable the engineer to make decision on different demands, an analytic hierarchy process (AHP) is implemented in the proposed procedure to determine the weight value of evaluation indexes. Three conflicting objectives: cost, quality and operation time are simultaneously optimized. An application sample is developed and its results are analyzed. The optimization results show that the hybrid algorithm is reliable and robust.
机译:零件加工方案的选择是一个重要的战略问题。它涉及多个相互矛盾的目标,例如成本,时间,质量,服务水平,资源利用等。选择始终受主观因素的影响,例如常规加工中决策者的知识和经验。本文提出了一种基于遗传算法(GA)的方法,以找到多目标数字加工方案选择的帕累托最优解集。为了处理多目标并允许工程师根据不同需求做出决策,在所提出的过程中实施了层次分析法(AHP),以确定评估指标的权重值。同时优化了三个相互矛盾的目标:成本,质量和运行时间。开发了一个应用程序样本并分析了其结果。优化结果表明,该混合算法可靠,鲁棒。

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