文献类型：会议论文

英文题名：Ant Colony Optimization with Local Search for Continuous Functions

作者：Qi, Chengming[1]

第一作者：亓呈明

通讯作者：Qi, CM[1]

机构：[1]Beijing Union Univ, Coll Automat, Beijing 100101, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Automat, Beijing 100101, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：International Conference on Industry, Information System and Material Engineering

会议日期：APR 16-17, 2011

会议地点：Guangzhou, PEOPLES R CHINA

语种：英文

外文关键词：Ant colony system; Continuous functions; Pareto local search

摘要：Ant algorithms are a recently developed, population-based approach which was inspired by the observation of the behavior of ant colonies. Based on the ant colony optimization idea, we present a hybrid ant colony system (ACS) coupled with a pareto local search (PLS) algorithm, named PACS, and apply to the continuous functions optimization. The ACS makes firstly variable range into grid. In local search, we use the PLS to escape local optimum. Computational results for some benchmark problems demonstrate that the proposed approach has the high search superior solution ability.