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» On the Brittleness of Evolutionary Algorithms
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CEC
2005
IEEE
16 years 5 days ago
Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies
Genetic algorithms (GAs) and evolution strategies (ESs) are two widely used evolutionary algorithms. The main differences between GAs and ESs lie in their representations and varia...
Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff
GECCO
2003
Springer
155views Optimization» more  GECCO 2003»
15 years 11 months ago
Adaptive Elitist-Population Based Genetic Algorithm for Multimodal Function Optimization
Abstract. This paper introduces a new technique called adaptive elitistpopulation search method for allowing unimodal function optimization methods to be extended to efficiently lo...
Kwong-Sak Leung, Yong Liang
ESCIENCE
2006
IEEE
15 years 10 months ago
A Differential Evolution Based Algorithm to Optimize the Radio Network Design Problem
In this paper we present a Differential Evolution based algorithm used to solve the Radio Network Design (RND) problem. This problem consists in determining the optimal locations ...
Silvio Priem-Mendes, Juan Antonio Gómez Pul...
EVOW
2006
Springer
15 years 10 months ago
Fast EAX Algorithm Considering Population Diversity for Traveling Salesman Problems
This paper proposes an evolutionary algorithm (EA) that is applied to the traveling salesman problem (TSP). Existing approximation methods to address the TSP known to be state-of-t...
Yuichi Nagata
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 10 months ago
Rotated test problems for assessing the performance of multi-objective optimization algorithms
This paper presents four rotatable multi-objective test problems that are designed for testing EMO (Evolutionary Multiobjective Optimization) algorithms on their ability in dealin...
Antony W. Iorio, Xiaodong Li