Hybrid Particle Swarm Optimization with Bat Algorithm
作者： Tien-Szu Pan , Thi-Kien Dao , Trong-The Nguyen , Shu-Chuan Chu
DOI: 10.1007/978-3-319-12286-1_5
关键词: Particle swarm optimization 、 Computer science 、 Optimization problem 、 Bat algorithm 、 Swarm intelligence 、 Multi-swarm optimization 、 Benchmark (computing) 、 Algorithm 、 Convergence (routing) 、 Firefly algorithm
摘要: In this paper, a communication strategy for hybrid Particle Swarm Optimization (PSO) with Bat Algorithm (BA) is proposed solving numerical optimization problems. work, several worst individuals of particles in PSO will be replaced the best BA after running some fixed iterations, and on contrary, poorer finest PSO. The communicating provides information flow to communicate bats BA. Six benchmark functions are used test behavior convergence, accuracy, speed approached method. results show that scheme increases convergence accuracy more than up 3% 47% respectively.
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