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多工序质量检验计划的多目标优化蚁群算法研究
引用本文:张赤斌,王海燕.多工序质量检验计划的多目标优化蚁群算法研究[J].中国机械工程,2006,17(11):1166-1169.
作者姓名:张赤斌  王海燕
作者单位:东南大学,南京,210096
基金项目:中国科学院资助项目;国家重点基础研究发展计划(973计划)
摘    要:针对常见的串行多工序抽样检验方式,建立了工序间质量水平传递模型和质量检验成本模型,提出基于Pareto解评价的多目标优化蚁群算法;通过定义多目标解与理想解的相对距离为蚁群算法的启发函数,激励蚁群搜索可行解空间并发现最优解集;应用多目标优化蚁群算法解决质量检验计划优化问题取得了较好效果。

关 键 词:检验计划  抽样检验  多目标优化  蚁群算法
文章编号:1004-132X(2006)11-1166-04
收稿时间:2005-01-25
修稿时间:2005-01-25

Research on Ant Colony Multi-object Optimization Algorithm Applied in Mutli-stage Quality Inspection Planning
Zhang Chibin,Wang Haiyan.Research on Ant Colony Multi-object Optimization Algorithm Applied in Mutli-stage Quality Inspection Planning[J].China Mechanical Engineering,2006,17(11):1166-1169.
Authors:Zhang Chibin  Wang Haiyan
Affiliation:Southeast University, Nanjing,210096
Abstract:The inspection cost transfer model and quality level model under sample inspection mode in series manufacturing were analyzed. The ant colony multi-object optimization method based on Pareto solution evaluation was proposed to realize optimization of inspection planning. Inspired with the defined distance between current and ideal solution, the ant colony algorithm is well suited for searching and finding the Pareto solution in reasonable solution set. The applications in practical inspection optimization show the availability of this algorithm.
Keywords:inspection planning  selective inspection  multi- object optimization  ant colony algorithm
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