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ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
14 years 3 months ago
Dejong Function Optimization by Means of a Parallel Approach to Fuzzified Genetic Algorithm
Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
Ebrahim Bagheri, Hossein Deldari
GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
13 years 10 months ago
Rigorous analyses of fitness-proportional selection for optimizing linear functions
Rigorous runtime analyses of evolutionary algorithms (EAs) mainly investigate algorithms that use elitist selection methods. Two algorithms commonly studied are Randomized Local S...
Edda Happ, Daniel Johannsen, Christian Klein, Fran...
ALP
1997
Springer
14 years 1 months ago
Optimal Non-deterministic Functional Logic Computations
Abstract. We show that non-determinism simplifies coding certain problems into programs. We define a non-confluent, but well-behaved class of rewrite systems for supporting non-...
Sergio Antoy
CORR
2010
Springer
115views Education» more  CORR 2010»
13 years 9 months ago
Optimal topological simplification of discrete functions on surfaces
We solve the problem of minimizing the number of critical points among all functions on a surface within a prescribed distance from a given input function. The result is achieved...
Ulrich Bauer, Carsten Lange, Max Wardetzky
GECCO
2003
Springer
155views Optimization» more  GECCO 2003»
14 years 2 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