基于Pareto遗传算法的切削用量优化
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国家高技术研究发展计划(863计划)资助项目(2007AA042005)、国家自然科学基金资助项目(50975193)和高等学校博士点专项科研基金资助项目(20060056016)


Optimization of Cutting Parameters Based on Pareto Genetic Algorithm
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    摘要:

    针对计算机辅助工艺规划中的切削用量决策问题,提出了一种基于Pareto遗传算法的切削用量优化算法。首先,以切削速度和进给量为优化变量,以切削效率和刀具耐用度为优化目标,通过对约束条件的分析,建立多目标优化模型。其次,改进选择算子,设置非劣解集以保存进化过程中用竞争法构造产生的Pareto最优解,从而保证算法的搜索方向;建立基于小生境技术的排挤机制以提高种群的多样性。然后,采用混合交叉算子和步长变异算子进行基因重组,经过若干次迭代,得到一个均匀分布于Pareto前沿的优化解集。最后,通过实例验证了该算法的可行性和有效性。

    Abstract:

    Based on the Pareto genetic algorithm, an algorithm was proposed for the cutting parameters selection and optimization to solve the decisionmaking problems of the cutting parameters in a computer aided process planning (CAPP) system. First, a multi-objective model was built by analysis of restraint with cutting speed and feed as optimization variables and cutting efficiency and the tool life as optimization objectives. Second, the selection operator was improved. In order to ensure the search direction, a non-inferior set was set up to save Pareto optimal solutions which were generated by competition during evolutionary processes. The crowing mechanism based on niche technology was established to keep population diversity. And then, genes were recombined by means of mixed crossover operator and step-size mutation operator and an optimal set which distributed uniformly along the Pareto front was obtained after a few times iteration. Experiments results showed that this algorithm was feasible and effective.

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刘 伟,王太勇.基于Pareto遗传算法的切削用量优化[J].农业机械学报,2011,42(2):220-224,234. Liu Wei, Wang Taiyong. Optimization of Cutting Parameters Based on Pareto Genetic Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(2):220-224,234.

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