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Abstract: Using Particle Swarm Optimization (PSO) for solving nonlinear, multimodal and non-di#erentiable optimization problems has gained increasing attention in recent years. Based on the social behavior and interaction of swarms like bird flocks, the method of Particle Swarm Optimization was introduced in 1995. While the behavior of the PSO algorithm is partially similar to other well known stochastic optimization methods such as Evolutionary Strategies or Simulated Annealing, it convinces by its... (Update)
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BibTeX entry: (Update)
@techreport{ torontodidunknown,
author = "{University of Toronto}",
title = "{UNKNOWN}",
number = "CSRI-274",
url = "citeseer.ist.psu.edu/741816.html" }
Citations (may not include all citations):663 Practical Optimization (context) - Gill, Murray et al. - 1981
73 Swarm Intelligence (context) - Kennedy, Eberhart - 2001
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18 Stochastic Ranking for Constrained Evolutionary Optimization - Runarsson, Yao - 2000
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2 Particle Swarm Optimization - Venter, Sobieszczanski-Sobieski - 2002
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1 Optimization of Nonlinear Mechanical Systems under Constrain.. (context) - Sedlaczek, Eberhard - 2004
1 Mathematical Computational Modeling (context) - Ingber - 1989
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