基于改进克隆选择算法的复杂系统测试选择

摘要

为了解决复杂系统测试优化选择问题,提出了一种基于改进克隆选择算法的测试选择方法.该方法针对测试选择问题的具体特点,对基本克隆选择算法进行了以下改进:采用二进制编码方式进行抗体编码,选用加性分段函数形式构建亲和度函数,利用混沌搜索优化初始种群的生成方式,并引入免疫网络的抗体抑制操作对抗体种群进行预处理.最后,以某实际系统为例进行了算法验证,实验结果表明:该方法搜索效率高,具有很强的全局和局部搜索能力,可有效解决复杂装备系统测试性设计中的测试优化选择问题.%In order to solve the problem of test selection for complex system, a method of test selection was proposed based on the enhanced clonal selection algorithm. Aiming at the characteristics of test selection, the basic clonal selection algorithm (BCSA) was improved as follows: the use of binary-coding method for antibody encoding, the selection of additive piecewise function form for constructing affinity function construction, the application of chaos search method in the population initialization, and the introduction of antibody suppression of immune network into BCSA for antibody population pretreatment. Finally, simulation experiments on a practical system were carried out to verify the algorithm. The experimental results indicate that the proposed algorithm is characterized by high search efficiency and strong abilities of local & global search, thereby dealing well with the test selection optimization for the testability design of complex system.