A Parallel Implementation of Particle Swarm Optimization Using Digital Pheromones

2006 ◽  
Author(s):  
Vijay Kalivarapu ◽  
Jung Leng Foo ◽  
Eliot Winer
Keyword(s):  
Particle Swarm Optimization ◽  
Parallel Implementation ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Digital Pheromones

scholarly journals A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-38 ◽  
Author(s):  
Yudong Zhang ◽  
Shuihua Wang ◽  
Genlin Ji
Keyword(s):  
Particle Swarm Optimization ◽  
Ant Colony Algorithm ◽  
Communication Theory ◽  
Parallel Implementation ◽  
Particle Swarm ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Swarm Optimization ◽  
Von Neumann ◽  
Automation Control

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

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