文献类型：期刊文献

英文题名：Traveling agent problem based on ant colony optimization algorithm

作者：Zhu, Shanhong[1,2]; Kuang, Tao[1]

第一作者：Zhu, Shanhong;朱珊虹

通讯作者：Zhu, Shanhong

机构：[1] Xinxiang University, School of Computer and Information Engineering, Henan, China; [2] Wuhan University, International School of Software, Wuhan, China

第一机构：新乡学院计算机与信息工程学院

年份：2014

卷号：32

期号：5

起止页码：4439-4446

外文期刊名：Energy Education Science and Technology Part A: Energy Science and Research

收录：EI(收录号：20150700515843);Scopus(收录号：2-s2.0-84922423152)

语种：英文

外文关键词：Algorithms - Ant colony optimization - Combinatorial optimization - Evolutionary algorithms - Feedback - Heuristic algorithms - Optimization

摘要：The traveling agent problem is a complex combinatorial optimization problem, which solves the problem of planning out an optimal migration path when agents migrate to several hosts. Ant colony algorithm is a new evolutionary algorithm, has the characteristic of parallelism, positive feedback and heuristic search. An ant colony algorithm is introduced to solve the traveling agent problem through modifying pheromone updating strategy. Experiment shows that the mobile agents can accomplish the computing tasks with much higher efficiency and in a shorter time. ? Sila Science. All rights reserved.