摘要
为了获得TSP问题的更优解,在求解TSP问题的细菌觅食算法基础上,通过在每次迭代中的趋向性操作之前,用淘汰选择和最优保持操作选择出当代的样本集并为其中的细菌做标记,提出了一种改进的细菌觅食搜索算法。之后对美国中部的10个城市以及Oliver的前30个和前50个城市的数据进行仿真,仿真结果表明,该算法求得的解比其他相应文献中算法求得的解更优,且该算法更容易收敛于最优解。因此,改进后的细菌觅食算法用来求解TSP问题是有效且可行的。
In order to get more optimal solution of traveling salesman problem （TSP）, based on essential bacterial foraging algorithm for solving TSP, this paper proposes an improved bacterial fora- ging algorithm. In this algorithm, a sample set is chosen by sieve selection and optimal maintaining operation before carrying on chemotaxis operation in every generation, and then the bacterium is marked. In the experiment, 10 cities in middle America and the first 30 cities in Oliver were cho- sen. Experimental results show that the proposed algorithm can achieve better results than other algorithms, and the proposed algorithm is also easier to converge. Thus, the the improved bacterial foraging algorithm used to solve TSP problem is effective and feasible.
出处
《广西大学学报（自然科学版）》
CAS
北大核心
2013年第6期1436-1443,共8页
Journal of Guangxi University（Natural Science Edition）
基金
国家自然科学基金资助项目(61100164
61173190)
教育部留学回国人员科研启动基金资助项目(教外司留[2012]1707号)
陕西省自然科学基础研究计划青年基金资助项目(2010JQ8034)
关键词
旅行商问题
细菌觅食算法
淘汰选择
样本集
标记细菌
traveling salesman problem
bacterial foraging algorithm
sieve selection
sample set
labeled bacteria
