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BMCBI
2006
146views more  BMCBI 2006»
13 years 10 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
CEC
2008
IEEE
14 years 4 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...
ESWA
2010
175views more  ESWA 2010»
13 years 8 months ago
A multi-objective PSO for job-shop scheduling problems
Most previous research into the job-shop scheduling problem has concentrated on finding a single optimal solution (e.g., makespan), even though the actual requirement of most prod...
D. Y. Sha, Hsing-Hung Lin
GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
14 years 1 months ago
Particle swarm with speciation and adaptation in a dynamic environment
This paper describes an extension to a speciation-based particle swarm optimizer (SPSO) to improve performance in dynamic environments. The improved SPSO has adopted several prove...
Xiaodong Li, Jürgen Branke, Tim Blackwell
GECCO
2003
Springer
245views Optimization» more  GECCO 2003»
14 years 3 months ago
A Non-dominated Sorting Particle Swarm Optimizer for Multiobjective Optimization
Abstract. This paper introduces a modified PSO, Non-dominated Sorting Particle Swarm Optimizer (NSPSO), for better multiobjective optimization. NSPSO extends the basic form of PSO...
Xiaodong Li