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GECCO
2009
Springer
121views Optimization» more  GECCO 2009»
14 years 2 months ago
Evolutionary algorithms and dynamic programming
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled...
Benjamin Doerr, Anton Eremeev, Christian Horoba, F...
GECCO
2003
Springer
14 years 26 days 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
2010
IEEE
13 years 8 months ago
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
Abstract-- Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic re...
Hui Li, Dario Landa Silva, Xavier Gandibleux
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 1 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
ROBOCUP
2004
Springer
114views Robotics» more  ROBOCUP 2004»
14 years 1 months ago
Evolutionary Gait-Optimization Using a Fitness Function Based on Proprioception
Abstract. This paper presents a new approach to optimize gait parameter sets using evolutionary algorithms. It separates the crossover-step of the evolutionary algorithm into an in...
Thomas Röfer