Move acceptance in local search metaheuristics for cross-domain search

Move acceptance in local search metaheuristics for cross-domain search •Classification of local search metaheuristics based on their move acceptance methods. •A concise overview of local search metaheuristics in relevant classes. •Cross-domain performance comparison of 8 local search metaheuristics from each class. •Simulated annealing (SA) has the best performance over 45 instances from 9 domains. •Parameters of SA needs re-tuning for each domain to achieve this performance. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Expert Systems with Applications Elsevier

Move acceptance in local search metaheuristics for cross-domain search

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0957-4174
D.O.I.
10.1016/j.eswa.2018.05.006
Publisher site
See Article on Publisher Site

Abstract

•Classification of local search metaheuristics based on their move acceptance methods. •A concise overview of local search metaheuristics in relevant classes. •Cross-domain performance comparison of 8 local search metaheuristics from each class. •Simulated annealing (SA) has the best performance over 45 instances from 9 domains. •Parameters of SA needs re-tuning for each domain to achieve this performance.

Journal

Expert Systems with ApplicationsElsevier

Published: Nov 1, 2018

References

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