EconPapers    
Economics at your fingertips  
 

Multiobjective Simulated Annealing: Principles and Algorithm Variants

Khalil Amine ()

Advances in Operations Research, 2019, vol. 2019, 1-13

Abstract: 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.

Date: 2019
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://downloads.hindawi.com/journals/AOR/2019/8134674.pdf (application/pdf)
http://downloads.hindawi.com/journals/AOR/2019/8134674.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaor:8134674

DOI: 10.1155/2019/8134674

Access Statistics for this article

More articles in Advances in Operations Research from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().

 
Page updated 2019-12-30
Handle: RePEc:hin:jnlaor:8134674