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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 11 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
GECCO
2008
Springer
107views Optimization» more  GECCO 2008»
13 years 8 months ago
The influence of scaling and assortativity on takeover times in scale-free topologies
In evolving systems, the topological characteristics of population structure have a pronounced impact on the rate of spread of advantageous alleles, and therefore affect selective...
Joshua L. Payne, Margaret J. Eppstein
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 1 months ago
An artificial immune network for multimodal function optimization on dynamic environments
Multimodal optimization algorithms inspired by the immune system are generally characterized by a dynamic control of the population size and by diversity maintenance along the sea...
Fabrício Olivetti de França, Fernand...
CDC
2009
IEEE
217views Control Systems» more  CDC 2009»
13 years 8 months ago
Discrete invasive weed optimization algorithm: application to cooperative multiple task assignment of UAVs
This paper presents a novel discrete population based stochastic optimization algorithm inspired from weed colonization. Its performance in a discrete benchmark, timecost trade-off...
Mohsen Ramezani Ghalenoei, Hossein Hajimirsadeghi,...
AAAI
1998
13 years 9 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge