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ISICA
2007
Springer
14 years 1 months ago
A New Evolutionary Decision Theory for Many-Objective Optimization Problems
In this paper the authors point out that the Pareto Optimality is unfair, unreasonable and imperfect for Many-objective Optimization Problems (MOPs) underlying the hypothesis that ...
Zhuo Kang, Lishan Kang, Xiufen Zou, Minzhong Liu, ...
GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
14 years 8 days ago
A probabilistic functional crossover operator for genetic programming
The original mechanism by which evolutionary algorithms were to solve problems was to allow for the gradual discovery of sub-solutions to sub-problems, and the automated combinati...
Josh C. Bongard
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer
ML
2010
ACM
119views Machine Learning» more  ML 2010»
13 years 5 months ago
A cooperative coevolutionary algorithm for instance selection for instance-based learning
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
Nicolás García-Pedrajas, Juan Antoni...