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PPSN
1998
Springer
14 years 4 days ago
Methods to Evolve Legal Phenotypes
Many optimization problems require the satisfaction of constraints in addition to their objectives. When using an evolutionary algorithm to solve such problems, these constraints c...
Tina Yu, Peter J. Bentley
GECCO
2009
Springer
119views Optimization» more  GECCO 2009»
14 years 17 days ago
Cooperative micro-differential evolution for high-dimensional problems
High–dimensional optimization problems appear very often in demanding applications. Although evolutionary algorithms constitute a valuable tool for solving such problems, their ...
Konstantinos E. Parsopoulos
IJCAI
1993
13 years 9 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
GECCO
2007
Springer
135views Optimization» more  GECCO 2007»
14 years 2 months ago
A cumulative evidential stopping criterion for multiobjective optimization evolutionary algorithms
In this work we present a novel and efficient algorithm– independent stopping criterion, called the MGBM criterion, suitable for Multiobjective Optimization Evolutionary Algorit...
Luis Martí, Jesús García, Ant...
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa