论文部分内容阅读
针对求解经典NP问题—旅行商难题(TSP),在标准细菌觅食算法上进行改进,提出了混合的细菌觅食算法(HBFA).一方面引入编码交叉思想对趋势步进行改进,使算法能更有效地处理离散优化问题;另一方面采用了自适应迁徙算子,使新生个体带有最优个体启发式信息的同时也增强了算法跳出局部最优能力.最后通过对TSPLIB中若干实例的实验仿真以及多种算法对比,验证了算法的可行性和有效性.
Aiming at solving classical NP problem - Traveling Salesman Problem (TSP) and improving on the standard bacteria foraging algorithm, a hybrid bacteria foraging algorithm (HBFA) is proposed.On the one hand, the code crossover idea is introduced to improve the trend step, More effective to deal with discrete optimization problems; the other hand, the use of adaptive migration operator, so that new individuals with the best individual heuristic information at the same time also enhances the algorithm to jump out of the local optimal ability.Finally through the TSPLIB in a number of examples Experimental simulation and comparison of a variety of algorithms to verify the feasibility and effectiveness of the algorithm.