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GECCO
2011
Springer
261views Optimization» more  GECCO 2011»
12 years 8 months ago
Spacing memetic algorithms
We introduce the Spacing Memetic Algorithm (SMA), a formal evolutionary model devoted to a systematic control of spacing (distances) among individuals. SMA uses search space dista...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
HIS
2009
13 years 2 months ago
Probability Diffused Particle Swarm Optimization
Premature convergence is a major problem of Particle Swarm Optimization (PSO).Although many strategies have been proposed, there is still some work needed to do in high-dimensional...
Qiuyan Qin, Zhihua Cui, Jianchao Zeng
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
13 years 8 months ago
The correlation-triggered adaptive variance scaling IDEA
It has previously been shown analytically and experimentally that continuous Estimation of Distribution Algorithms (EDAs) based on the normal pdf can easily suffer from premature ...
Jörn Grahl, Peter A. N. Bosman, Franz Rothlau...
GECCO
2010
Springer
151views Optimization» more  GECCO 2010»
13 years 9 months ago
Sustaining behavioral diversity in NEAT
Niching schemes, which sustain population diversity and let an evolutionary population avoid premature convergence, have been extensively studied in the research field of evoluti...
Hirotaka Moriguchi, Shinichi Honiden
GECCO
2010
Springer
148views Optimization» more  GECCO 2010»
13 years 9 months ago
Guarding against premature convergence while accelerating evolutionary search
The fundamental dichotomy in evolutionary algorithms is that between exploration and exploitation. Recently, several algorithms [8, 9, 14, 16, 17, 20] have been introduced that gu...
Josh C. Bongard, Gregory S. Hornby
GECCO
2003
Springer
13 years 9 months ago
Optimization Using Particle Swarms with Near Neighbor Interactions
This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. ...
Kalyan Veeramachaneni, Thanmaya Peram, Chilukuri K...
GECCO
2003
Springer
13 years 9 months ago
HEMO: A Sustainable Multi-objective Evolutionary Optimization Framework
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-mo...
Jianjun Hu, Kisung Seo, Zhun Fan, Ronald C. Rosenb...
EPIA
2007
Springer
13 years 10 months ago
Improving Evolutionary Algorithms with Scouting
The goal of an Evolutionary Algorithm(EA) is to find the optimal solution to a given problem by evolving a set of initial potential solutions. When the problem is multi-modal, an ...
Konstantinos Bousmalis, Gillian M. Hayes, Jeffrey ...
EVOW
2009
Springer
13 years 11 months ago
Stochastic Local Search Techniques with Unimodal Continuous Distributions: A Survey
In continuous black-box optimization, various stochastic local search techniques are often employed, with various remedies for fighting the premature convergence. This paper surve...
Petr Posík