基于均匀免疫优化算法的最大团问题求解

最大团问题是一种典型的组合优化问题,具有广泛的应用背景。针对最大团问题的NP特性,提出了一种基于免疫克隆优化的智能求解算法。描述了最大团问题的数学模型,设计了求解最大团问题的抗体编码、亲和度函数、变异算子及抗体修正方法。在免疫克隆参数设置时,将其描述为多因素多水平的均匀设计,减少了设置参数的实验次数。通过最大团问题的基准算例进行了实验。结果表明,本算法求解效果较好,并且求解速度较快。

A uniform immune clone based intelligent optimization algorithm to solve the maximum clique problem

The maximum clique problem is a typical combinatorial optimization problem,which has wide application background.For the NP characteristic of the maximum clique problem, an immune clone based on intelligent optimization algorithm is proposed to solve it. The mathematical model of the maximum clique problem is described.For solving the maximum clique problem,antibody encoding, affinity function, mutation operator and antibody correction method are designed. To reduce  the number of parameter setting for the experiment, it is converted into a uniform design problem of multi factor and multi level.The Benchmark experimental results show that the algorithm has better performance and rapid solving speed.