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Multiobjective Simulated Annealing: Principles and Algorithm Variants
Author
Source
Advances in Operations Research
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-05-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
Simulated annealing is a stochastic local search method, initially introduced for global combinatorial mono-objective optimisation problems, allowing gradual convergence to a near-optimal solution.
An extended version for multiobjective optimisation has been introduced to allow a construction of near-Pareto optimal solutions by means of an archive that catches nondominated solutions while exploring the feasible domain.
Although simulated annealing provides a balance between the exploration and the exploitation, multiobjective optimisation problems require a special design to achieve this balance due to many factors including the number of objective functions.
Accordingly, many variants of multiobjective simulated annealing have been introduced in the literature.
This paper reviews the state of the art of simulated annealing algorithm with a focus upon multiobjective optimisation field.
American Psychological Association (APA)
Amine, Khalil. 2019. Multiobjective Simulated Annealing: Principles and Algorithm Variants. Advances in Operations Research،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1121537
Modern Language Association (MLA)
Amine, Khalil. Multiobjective Simulated Annealing: Principles and Algorithm Variants. Advances in Operations Research No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1121537
American Medical Association (AMA)
Amine, Khalil. Multiobjective Simulated Annealing: Principles and Algorithm Variants. Advances in Operations Research. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1121537
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121537