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Simulated annealing

Known as: SA, Simulated annealling, Generalized simulated annealing 
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic… 
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Related topics

Related topics

50 relations
Ant colony optimization algorithmsBoltzmann machineCladogramCrystal structure prediction

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Genetic simulated annealing algorithm for task scheduling based on cloud computing environment
Scheduling is a very important part of the cloud computing system. This paper introduces an optimized algorithm for task… 
Review
2009
Review
2009
Recent Progress in Polymer Solar Cells: Manipulation of Polymer:Fullerene Morphology and the Formation of Efficient Inverted Polymer Solar Cells
Polymer morphology has proven to be extremely important in determining the optoelectronic properties in polymer‐based devices… 
2009
2009
Using Simulated Annealing for Task Scheduling in Distributed Systems
Task scheduling is one of the key factors in a distributed system. That is, how proper allocating the tasks to the processor of… 
Highly Cited
2006
Highly Cited
2006
Robot Path Planning Based on Artificial Potential Field Approach with Simulated Annealing
The artificial potential field (APF) approach provides a simple and effective motion planning method for practical purpose… 
Highly Cited
2002
Highly Cited
2002
Using simulated annealing for resource allocation
Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and… 
Highly Cited
1999
Highly Cited
1999
Phase balancing using simulated annealing
Deregulation eliminates the boundary of the territory of the monopoly power industry. Competition forces utilities to improve… 
Highly Cited
1998
Highly Cited
1998
Fitting models predicting dates of flowering of temperate‐zone trees using simulated annealing
The aim of the present study was to test the four commonly used models to predict the dates of flowering of temperatezone trees… 
Highly Cited
1997
Highly Cited
1997
DYNAMIC FINITE ELEMENT MODEL UPDATING USING SIMULATED ANNEALING AND GENETIC ALGORITHMS
Abstract Dynamic finite element (FE) model updating may be considered as an optimisation process. Over the past few years, two… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Highly Cited
1993
Highly Cited
1993
Channel assignment for cellular radio using simulated annealing
The channel assignment problem, i.e. the task of assigning the channels to the radio base stations in a spectrum-efficient way… 
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