NEW BINARY PARTICLE SWARM OPTIMIZATION WITH IMMUNITY-CLONAL ALGORITHM
作者： EL-Gammal Dina , Amr Badr , Mostafa Abd El Azeim
DOI: 10.3844/JCSSP.2013.1534.1542
关键词: Particle swarm optimization 、 Imperialist competitive algorithm 、 Computer science 、 Knapsack problem 、 Metaheuristic 、 Meta-optimization 、 Algorithm 、 Mathematical optimization 、 Firefly algorithm 、 Derivative-free optimization 、 Multi-swarm optimization
摘要: Particle Swarm Optimization used to solve a continu ous problem and has been shown perform well however, binary version still some problems. In order these problems new technique call ed New Binary using Immunity-Clonal Algorithm (NPSOCLA) is proposed This proposes updating strategy update the position vector in (BPSO), which further combined with improve optimization ability. To investigate performanc e of algorithm, multidimensional 0/1 knapsack are as test benchmarks. The experiment results demonstrate that Binar y Immunity Clonal Algorithm, found optimum solution for 53 5 8 0/1knapsack
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