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

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

2006-01-31

arxiv.org/abs/cs/0601132v1

Computer Science

Artificial Intelligence

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-353631