NEW BINARY PARTICLE SWARM OPTIMIZATION WITH IMMUNITY-CLONAL ALGORITHM | Science Publications

Journal of Computer Science

Mostafa Abd El Azeim¹  Dina EL-Gammal¹  Amr Badr¹ 

关键词: Immunity-Clonal Algorithm;    Particle Swarm Optimization;    Binary Particle Swarm Optimization;   

DOI  :  10.3844/jcssp.2013.1534.1542

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

Particle Swarm Optimization used to solve a continuous problem and has been shown to perform well however, binary version still has some problems. In order to solve these problems a new technique called New Binary Particle Swarm Optimization using Immunity-Clonal Algorithm (NPSOCLA) is proposed This Algorithm proposes a new updating strategy to update the position vector in Binary Particle Swarm Optimization (BPSO), which further combined with Immunity-Clonal Algorithm to improve the optimization ability. To investigate the performance of the new algorithm, the multidimensional 0/1 knapsack problems are used as a test benchmarks. The experiment results demonstrate that the New Binary Particle Swarm Optimization with Immunity Clonal Algorithm, found the optimum solution for 53 of the 58 multidimensional 0/1knapsack problems.

【 授权许可】

Unknown