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GECCO
1999
Springer
158views Optimization» more  GECCO 1999»
13 years 12 months ago
Coevolutionary Genetic Algorithms for Solving Dynamic Constraint Satisfaction Problems
In this paper, we discuss the adaptability of Coevolutionary Genetic Algorithms on dynamic environments. Our CGA consists of two populations: solution-level one and schema-level o...
Hisashi Handa, Osamu Katai, Tadataka Konishi, Mits...
TEC
2010
132views more  TEC 2010»
13 years 2 months ago
A Hybrid Evolutionary Approach to the Nurse Rostering Problem
Nurse rostering is a difficult search problem with many constraints. In the literature, a number of approaches have been investigated including penalty function methods to tackle t...
Ruibin Bai, Edmund K. Burke, Graham Kendall, Jingp...
GECCO
2006
Springer
447views Optimization» more  GECCO 2006»
13 years 11 months ago
Candlestick stock analysis with genetic algorithms
Candlestick analysis, a form of stock market technical analysis, is well suited for use with a genetic search algorithm. This paper explores an implementation of marrying these tw...
Peter Belford
GECCO
2000
Springer
131views Optimization» more  GECCO 2000»
13 years 11 months ago
A Genetic Algorithm with Tabu Search for Multimodal and Multiobjective Function Optimization
The integration of genetic algorithms (GAs) and tabu search is one of traditional problems in function optimization in the GA literature. However, most proposed methods have utili...
Setsuya Kurahashi, Takao Terano
CEC
2008
IEEE
14 years 2 months ago
Dynamic adaptation and multiobjective concepts in a particle swarm optimizer for constrained optimization
— In this paper, we propose a novel approach to solve constrained optimization problems based on particle swarm optimization (PSO). First, an empirical comparison of the most pop...
Jorge Isacc Flores-Mendoza, Efrén Mezura-Mo...