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GECCO
2005
Springer
128views Optimization» more  GECCO 2005»
13 years 10 months ago
Hybrid multiobjective genetic algorithm with a new adaptive local search process
This paper is concerned with a specific brand of evolutionary algorithms: Memetic algorithms. A new local search technique with an adaptive neighborhood setting process is introdu...
Salem F. Adra, Ian Griffin, Peter J. Fleming
GECCO
2003
Springer
13 years 10 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...
CEC
2007
IEEE
13 years 11 months ago
How well do multi-objective evolutionary algorithms scale to large problems
Abstract— In spite of large amount of research work in multiobjective evolutionary algorithms, most have evaluated their algorithms on problems with only two to four objectives. ...
Kata Praditwong, Xin Yao
NIPS
2004
13 years 6 months ago
Convergence and No-Regret in Multiagent Learning
Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...
Michael H. Bowling
CSC
2006
13 years 6 months ago
A New Migration Model For Distributed Genetic Algorithms
Genetic algorithms are heuristic search algorithm used in science, engineering and many other areas. They are powerful but slow because of their evolutionary nature that mimics th...
Taisir Eldos