Research Article Open Access

NEW BINARY PARTICLE SWARM OPTIMIZATION WITH IMMUNITY-CLONAL ALGORITHM

Dina EL-Gammal1, Amr Badr2 and Mostafa Abd El Azeim3
  • 1 MISR University for Science and Technology, Egypt
  • 2 Cairo University, Egypt
  • 3 , Egypt

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 of Computer Science
Volume 9 No. 11, 2013, 1534-1542

DOI: https://doi.org/10.3844/jcssp.2013.1534.1542

Submitted On: 16 September 2013 Published On: 30 September 2013

How to Cite: EL-Gammal, D., Badr, A. & Azeim, M. A. E. (2013). NEW BINARY PARTICLE SWARM OPTIMIZATION WITH IMMUNITY-CLONAL ALGORITHM. Journal of Computer Science, 9(11), 1534-1542. https://doi.org/10.3844/jcssp.2013.1534.1542

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Keywords

  • Immunity-Clonal Algorithm
  • Particle Swarm Optimization
  • Binary Particle Swarm Optimization