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» On the convergence of multi-parent genetic algorithms
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GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
13 years 11 months ago
An efficient multi-objective evolutionary algorithm with steady-state replacement model
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
Dipti Srinivasan, Lily Rachmawati
AEI
1999
134views more  AEI 1999»
13 years 7 months ago
Automatic design synthesis with artificial intelligence techniques
Design synthesis represents a highly complex task in the field of industrial design. The main difficulty in automating it is the definition of the design and performance spaces, i...
Francisco J. Vico, Francisco J. Veredas, Jos&eacut...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 1 months ago
Distribution replacement: how survival of the worst can out perform survival of the fittest
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Howard Tripp, Phil Palmer
GECCO
2008
Springer
113views Optimization» more  GECCO 2008»
13 years 8 months ago
Genetic programming based automatic gait generation for quadruped robots
This paper introduces a new approach to develop a fast gait for quadruped robot using genetic programming (GP). Several recent approaches have focused on the genetic algorithm (GA...
Kisung Seo, Soohwan Hyun
GECCO
2010
Springer
158views Optimization» more  GECCO 2010»
13 years 11 months ago
Efficiently evolving programs through the search for novelty
A significant challenge in genetic programming is premature convergence to local optima, which often prevents evolution from solving problems. This paper introduces to genetic pro...
Joel Lehman, Kenneth O. Stanley