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» A parallel search algorithm for CLNS addition optimization
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GECCO
2004
Springer
131views Optimization» more  GECCO 2004»
15 years 6 months ago
PolyEDA: Combining Estimation of Distribution Algorithms and Linear Inequality Constraints
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
Jörn Grahl, Franz Rothlauf
114
Voted
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
15 years 6 months ago
A hardware pipeline for function optimization using genetic algorithms
Genetic Algorithms (GAs) are very commonly used as function optimizers, basically due to their search capability. A number of different serial and parallel versions of GA exist. ...
Malay Kumar Pakhira, Rajat K. De
103
Voted
IPPS
2007
IEEE
15 years 7 months ago
Optimizing Sorting with Machine Learning Algorithms
The growing complexity of modern processors has made the development of highly efficient code increasingly difficult. Manually developing highly efficient code is usually expen...
Xiaoming Li, María Jesús Garzar&aacu...
ANTSW
2008
Springer
15 years 2 months ago
Adaptive Particle Swarm Optimization
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...
Zhi-hui Zhan, Jun Zhang
GECCO
2005
Springer
109views Optimization» more  GECCO 2005»
15 years 6 months ago
A hybrid evolutionary algorithm for the p-median problem
A hybrid evolutionary algorithm (EA) for the p-median problem consist of two stages, each of which is a steady-state hybrid EA. These EAs encode selections of medians as subsets o...
István Borgulya