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GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
15 years 6 months ago
Stochastic local search in continuous domains: questions to be answered when designing a novel algorithm
Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains ...
Petr Posik
ICGA
1997
133views Optimization» more  ICGA 1997»
15 years 5 months ago
Messy Genetic Algorithms for Subset Feature Selection
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...
GECCO
2005
Springer
101views Optimization» more  GECCO 2005»
15 years 9 months ago
Measuring mobility and the performance of global search algorithms
The global search properties of heuristic search algorithms are not well understood. In this paper, we introduce a new metric, mobility, that quantifies the dispersion of local o...
Monte Lunacek, L. Darrell Whitley, James N. Knight
NICSO
2010
Springer
15 years 8 months ago
Accelerated Genetic Algorithms with Markov Chains
t] Based on the mutation matrix formalism and past statistics of genetic algorithm, a Markov Chain transition probability matrix is introduced to provide a guided search for comple...
Guan Wang, Chen Chen, Kwok Yip Szeto
CEC
2005
IEEE
15 years 9 months 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