Journal of Computer Science

NEW BINARY PARTICLE SWARM OPTIMIZATION WITH IMMUNITY-CLONAL ALGORITHM

Dina EL-Gammal, Amr Badr and Mostafa Abd El Azeim

DOI : 10.3844/jcssp.2013.1534.1542

Journal of Computer Science

Volume 9, Issue 11

Pages 1534-1542

Abstract

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.

Copyright

© 2013 Dina EL-Gammal, Amr Badr and Mostafa Abd El Azeim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.