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GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 2 months ago
Observing the swarm behaviour during its evolutionary design
Evolutionary Algorithms (EAs) can be used for designing Particle Swarm Optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By...
Laura Diosan, Mihai Oltean
EC
2000
96views ECommerce» more  EC 2000»
13 years 8 months ago
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
David A. van Veldhuizen, Gary B. Lamont
TEC
2008
115views more  TEC 2008»
13 years 8 months ago
Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
GECCO
2005
Springer
197views Optimization» more  GECCO 2005»
14 years 1 months ago
Breeding swarms: a GA/PSO hybrid
Abstract. In this paper we propose a novel hybrid (GA/PSO) algorithm, Breeding Swarm, combining the strengths of particle swarm optimization with genetic algorithms. The hybrid alg...
Matthew Settles, Terence Soule
GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
14 years 1 months ago
Statistical analysis of heuristics for evolving sorting networks
Designing efficient sorting networks has been a challenging combinatorial optimization problem since the early 1960’s. The application of evolutionary computing to this problem ...
Lee K. Graham, Hassan Masum, Franz Oppacher