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GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
15 years 8 months ago
A multi-start quantum-inspired evolutionary algorithm for solving combinatorial optimization problems
Quantum-inspired evolutionary algorithms (QIEAs), as a subset of evolutionary computation, are based on the principles of quantum computing such as quantum bits and quantum superp...
Parvaz Mahdabi, Saeed Jalili, Mahdi Abadi
GECCO
2008
Springer
103views Optimization» more  GECCO 2008»
15 years 8 months ago
Empirical investigations on parallel competent genetic algorithms
This paper empirically investigates parallel competent genetic algorithms (cGAs) [4]. cGAs, such as BOA [21], LINCGA [15], D5 -GA [28], can solve GA-difficult problems by automati...
Miwako Tsuji, Masaharu Munetomo, Kiyoshi Akama
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
15 years 8 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
GECCO
2008
Springer
129views Optimization» more  GECCO 2008»
15 years 8 months ago
Exploiting the path of least resistance in evolution
Hereditary Repulsion (HR) is a selection method coupled with a fitness constraint that substantially improves the performance and consistency of evolutionary algorithms. This als...
Gearoid Murphy, Conor Ryan
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
15 years 8 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb
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