Multiobjective Simulated Annealing: Principles and Algorithm Variants

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ID: 7772
2019
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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.
Reference Key
khalil2019multiobjectiveadvances Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Amine, Khalil;Amine, Khalil;
Journal advances in operations research
Year 2019
DOI
10.1155/2019/8134674
URL
https://www.hindawi.com/journals/aor/2019/8134674/abs/
Keywords Keywords not found

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