@article {10.3844/jcssp.2013.1534.1542,
article_type = {journal},
title = {NEW BINARY PARTICLE SWARM OPTIMIZATION WITH IMMUNITY-CLONAL ALGORITHM},
author = {EL-Gammal, Dina and Badr, Amr and Azeim, Mostafa Abd El},
volume = {9},
number = {11},
year = {2013},
month = {Sep},
pages = {1534-1542},
doi = {10.3844/jcssp.2013.1534.1542},
url = {https://thescipub.com/abstract/jcssp.2013.1534.1542},
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.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}