改进蜂群算法求解大规模着色瓶颈旅行商问题

Improved artificial bee colony algorithm for large scale colored bottleneck traveling salesman problem

在智能交通、多任务协作等领域,用着色瓶颈旅行商问题(CBTSP,colored bottleneck traveling salesman problem)所构建模型尺度易趋向于大规模,因此有必要研究大规模CBTSP及其求解算法。本文将一种改进蜂群算法(IABC,improved artificial bee colony algorithm)应用于求解大规模CBTSP。IABC首先运用m-tour编码方法生成问题的解,然后使用产生邻近解(GNS,generate neighboring solution)优化蜂群算法求解该问题,GNS通过采用删除和重插入操作来产生新的解,并在该过程中实现对已有解的优化。实验表明IABC求解大规模CBTSP问题的求解质量优于其他对比算法。

In the fields such as intelligent transport and multiple tasks cooperation,the model scale constructed by colored bottleneck traveling salesman problem(CBTSP)tends to large scale,and therefore it is necessary to study the large scale CBTSP and its algorithms.An improved artificial bee colony algorithm(IABC)was applied to solve the large scale CBTSP.IABC employed generating neighboring solution(GNS)to improve artificial bee colony algorithm for CBTSP.GNS generated new solution by deletion and reinsertion operations,during this process,and it can optimized the existed solution for this problem.Experiments show that IABC can demonstrate better solution quality than other compared algorithms for large scale CBTSP.