Computer Science, abstract
cs.AI/0601132

From: Reza Rastegar [view email]
Date: Tue, 31 Jan 2006 07:10:45 GMT   (193kb)

A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms

Authors: R. Rastegar, M. R. Meybodi
Subj-class: Artificial Intelligence; Neural and Evolutionary Computing
The Estimation of Distribution Algorithm is a new class of population based search methods in that a probabilistic model of individuals is estimated based on the high quality individuals and used to generate the new individuals. In this paper we compute 1) some upper bounds on the number of iterations required for global convergence of EDA 2) the exact number of iterations needed for EDA to converge to global optima.

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... A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms R. Rastegar M. R. Meybodi Computer Engineering Department, Amirkabir University, Tehran, Iran {rrastegar, meybodi@ce.aut.ac.ir} Abstract. The Estimation of Distribution Algorithm is a new class of population based search methods in that a ...
... E.: BOA: the Bayesian Optimization Algorithm. In: the Genetic and Evolutionary Computation Conference, Morgan Kaufmann Publishers, (1999) 525-532 14. Rastegar, R., Meybodi, M.R.: LAEDA, A New Evolutionary Algorithm using Learning Automata. In: The 9 th Annual ...

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