WSC
2004
13 years 6 months ago
2004
This paper presents preliminary work done on simulationbased optimization of a stochastic material-dispatching system in a retailer network. The problem we consider is one of dete...
WSC
2004
13 years 6 months ago
2004
In this paper we describe a methodology that includes the complementary use of simulated annealing and response surface methodology (RSM). The methodology was developed for analys...
WSC
2004
13 years 6 months ago
2004
This paper presents a new meta heuristic algorithm based on the search method called simulated annealing, and its application to solving multi objective simulation optimization pr...
IJCAI
2001
13 years 6 months ago
2001
Using a distributed algorithm rather than a centralized one can be extremely beneficial in large search problems. In addition, the incorporation of machine learning techniques lik...
AAAI
2004
13 years 6 months ago
2004
Scheduling observations by coordinated fleets of Earth Observing Satellites (EOS) involves large search spaces, complex constraints and poorly understood bottlenecks; conditions w...
HIS
2008
13 years 6 months ago
2008
This article presents an algorithm for the automatic detection of circular shapes from complicated and noisy images. The algorithm is based on a hybrid technique composed of simul...
CBMS
2005
IEEE
13 years 6 months ago
2005
IEEE
In gene expression data a bicluster is a subset of genes and a subset of conditions which show correlating levels of expression. However, the problem of finding significant biclu...
AAAI
2007
13 years 7 months ago
2007
This paper reconsiders the travelling tournament problem, a complex sport-scheduling application which has attracted significant interest recently. It proposes a population-based...
AAAI
2008
13 years 7 months ago
2008
This paper presents a fast simulated annealing framework for combining multiple clusterings (i.e. clustering ensemble) based on some measures of agreement between partitions, whic...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
Simulated annealing and the (1+1) EA, a simple evolutionary algorithm, are both general randomized search heuristics that optimize any objective function with probability