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Cooperative coevolutionary differential evolution with improved augmented Lagrangian to solve constrained optimisation problems

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posted on 2024-11-23, 10:06 authored by Behrooz Ghasemishabankareh, Xiaodong LiXiaodong Li, Melih OzlenMelih Ozlen
In constrained optimisation, the augmented Lagrangian method is considered as one of the most effective and efficient methods. This paper studies the behaviour of augmented Lagrangian function (ALF) in the solution space and then proposes an improved augmented Lagrangian method. We have shown that our proposed method can overcome some of the drawbacks of the conventional augmented Lagrangian method. With the improved augmented Lagrangian approach, this paper then proposes a cooperative coevolutionary differential evolution algorithm for solving constrained optimisation problems. The proposed algorithm is evaluated on a set of 24 well-known benchmark functions and five practical engineering problems. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art algorithms with respect to solution quality as well as efficiency.

Funding

Unlocking the potential for linear and discrete optimisation in knot theory and computational topology

Australian Research Council

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History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.ins.2016.06.047
  2. 2.
    ISSN - Is published in 00200255

Journal

Information Sciences

Volume

369

Start page

441

End page

456

Total pages

16

Publisher

Elsevier

Place published

United States

Language

English

Copyright

© 2016 Elsevier Inc.

Former Identifier

2006067170

Esploro creation date

2020-06-22

Fedora creation date

2016-10-26

Open access

  • Yes

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