文献类型：会议论文

英文题名：Solving 0-1 Knapsack Problem Based on Immune Clonal Algorithm and Ant Colony Algorithm

作者：Zhao Fang[1];Ma Yu-Lei[1];Zhang Jun-Peng[2]

第一作者：赵芳

通讯作者：Zhao, F[1]

机构：[1]Xinxiang Univ, Dept Comp & Informat Engn, Xinxiang 453003, Peoples R China;[2]Henan Zhumadian Power Supply Co, Zhumadian 463000, Peoples R China

第一机构：新乡学院计算机与信息工程学院

通讯机构：[1]corresponding author), Xinxiang Univ, Dept Comp & Informat Engn, Xinxiang 453003, Peoples R China.|[1107118]新乡学院计算机与信息工程学院;[11071]新乡学院;

会议论文集：International Conference on Communications, Electronics and Automation Engineering

会议日期：AUG 23-25, 2012

会议地点：Xian, PEOPLES R CHINA

语种：英文

外文关键词：0-1 knapsack problem; Ant colony algorithm; Antibody immune clonal algorithm

摘要：The 0/1 Knapsack Problem is a very well known and it appears in many real life world with different application. In this paper, we propose a new hybrid algorithm which inspired from Ant Colony Algorithm (ACA) and Antibody Immune Clonal Algorithm (AICA) to tackle 0-1 knapsack problem. ACA algorithm which benefit from its positive strategy has a great performance in local search, but it is prone to stagnation; AICA algorithm can search in a greater range, but it is lack of sufficient utilization of feedback information of system. So, we take full advantages of the ability of searching and the diversity which they provide respectively. Some parameters of the algorithm and the comparison with other algorithms have been performed. The experimental results show that the proposed algorithm is a perfect hybrid algorithm with higher performance.