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» Unsupervised Problem Decomposition Using Genetic Programming
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SIGADA
2004
Springer
15 years 3 months ago
Comparative analysis of genetic algorithm implementations
Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is “evolved” from a set of potential solutio...
Robert Soricone, Melvin Neville
CEC
2005
IEEE
15 years 3 months ago
Evolving dispatching rules for solving the flexible job-shop problem
We solve the Flexible Job-Shop Problem (FJSP) by using dispatching rules discovered through Genetic Programming (GP). While Simple Priority Rules (SPR) have been widely applied in ...
Nhu Binh Ho, Joc Cing Tay
IJCNN
2006
IEEE
15 years 3 months ago
Generalizing Independent Component Analysis for Two Related Data Sets
— We introduce in this paper methods for finding mutually corresponding dependent components from two different but related data sets in an unsupervised (blind) manner. The basi...
Juha Karhunen, Tomas Ukkonen
CORR
2008
Springer
173views Education» more  CORR 2008»
14 years 9 months ago
Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
Fangwen Fu, Mihaela van der Schaar
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
14 years 10 months ago
Genetic algorithms for mentor-assisted evaluation function optimization
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an approp...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...