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GECCO
2003
Springer
155views Optimization» more  GECCO 2003»
14 years 3 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
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 11 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...
PPSN
1992
Springer
14 years 1 months ago
Nonstationary Function Optimization using the Structured Genetic Algorithm
In this paper, we describe the application of a new type of genetic algorithm called the Structured Genetic Algorithm (sGA) for function optimization in nonstationary environments...
Dipankar Dasgupta, Douglas R. McGregor
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
14 years 3 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
FOCS
2006
IEEE
14 years 3 months ago
Fast Algorithms for Logconcave Functions: Sampling, Rounding, Integration and Optimization
We prove that the hit-and-run random walk is rapidly mixing for an arbitrary logconcave distribution starting from any point in the support. This extends the work of [26], where t...
László Lovász, Santosh Vempal...