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» Evolutionary Algorithms for the Satisfiability Problem
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GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
15 years 5 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
GECCO
2005
Springer
101views Optimization» more  GECCO 2005»
15 years 8 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
EMO
2005
Springer
126views Optimization» more  EMO 2005»
15 years 8 months ago
The Evolution of Optimality: De Novo Programming
Abstract. Evolutionary algorithms have been quite effective in dealing with single-objective “optimization” while the area of Evolutionary Multiobjective Optimization (EMOO) h...
Milan Zeleny
GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
15 years 7 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
CISIM
2008
IEEE
15 years 9 months ago
Tuning Struggle Strategy in Genetic Algorithms for Scheduling in Computational Grids
Job Scheduling on Computational Grids is gaining importance due to the need for efficient large-scale Grid-enabled applications. Among different optimization techniques addressed ...
Fatos Xhafa, Bernat Duran, Ajith Abraham, Keshav P...