In order to solve the testability distribution problem,a multi-objective optimization model was proposed.Based on the mathematics analyses,the model was used to optimize the system test expenses and testability level.After the multi-objective problem was transformed to single-objective problem,the model was solved by floating-coding genetic algorithm.The method can improve the result’s precision,be programmed to solve the model in the condition of many more distribution parameters,and meet different distribution needs through changing the weight of every objective function.In the end,the testability indexes of a construction machinery hydraulic system were distributed by the method. The results indicate that the method can trade off the system testability and test expenses effectively, and distribute testability indexes reasonably by the restriction of system and its subsystems (or units) testability.

针对测试性分配问题,在测试性分配数学分析的基础上提出了一种以全生命周期费用和测试性水平为目标的多目标优化模型。在求解模型时,按照权重将多目标问题转化为单目标优化问题后采用浮点编码遗传算法求解,该模型有利于提高求解精度,尤其在分配参数较多的情况下,可以改变各目标权重值,满足不同的分配需求。最后应用该模型对某型工程机械液压系统进行实际分配,分析结果表明该模型能够对系统测试性和全生命周期费用进行有效权衡,在系统及其子系统（或单元）测试性指标约束下进行合理的测试性分配。

可测试性, 测试性分配, 多目标优化, 浮点编码遗传算法