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What is Particle Swarm Optimizer/Optimization

Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems
Particle Swarm Optimizer/Optimization, which is one of the evolutionary computation techniques, was invented by Eberhart and Kennedy in 1995. It is a population-based stochastic algorithm modeled on the social behaviors observed in flocking birds. Each particle, which represents a solution, flies through the search space with a velocity that is dynamically adjusted according to its own and its companion's historical behaviors.
Published in Chapter:
Experimental Study on Boundary Constraints Handling in Particle Swarm Optimization
Shi Cheng (Shaanxi Normal University, China) and Yuhui Shi (Southern University of Science and Technology, China)
DOI: 10.4018/978-1-7998-3222-5.ch011
Abstract
With an improper boundary constraints handling method, particles may get “stuck in” the boundary. Premature convergence means that an algorithm has lost its ability of exploration. Population diversity (PD) is an effective way to monitor an algorithm's ability for exploration and exploitation. Through the PD measurement, useful search information can be obtained. PSO with a different topology structure and different boundary constraints handling strategy will have a different impact on particles' exploration and exploitation ability. In this chapter, the phenomenon of particles gets “stuck in” the boundary in PSO and is experimentally studied and reported. The authors observe the position diversity time-changing curves of PSOs with different topologies and different boundary constraints handling techniques and analyze the impact of these strategies on the algorithm's ability of exploration and exploitation.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Population Diversity of Particle Swarm Optimization Algorithm on Solving Single and Multi-Objective Problems
Particle Swarm Optimizer/Optimization, which is one of the evolutionary computation techniques, was invented by Eberhart and Kennedy in 1995. It is a population-based stochastic algorithm modeled on the social behaviors observed in flocking birds. Each particle, which represents a solution, flies through the search space with a velocity that is dynamically adjusted according to its own and its companion's historical behaviors.
Full Text Chapter Download: US $37.50 Add to Cart
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