Cheng, T., Chen, M., Fleming, P.J. orcid.org/0000-0001-9837-8404 et al. (2 more authors) (2017) A novel hybrid teaching learning based multi-objective particle swarm optimization. Neurocomputing, 222. pp. 11-25. ISSN 0925-2312
Abstract
How to obtain a good convergence and well-spread optimal Pareto front is still a major challenge for most meta-heuristic multi-objective optimization (MOO) methods. In this paper, a novel hybrid teaching learning based particle swarm optimization (HTL-PSO) with circular crowded sorting (CCS), named HTL-MOPSO, is proposed for solving MOO problems. Specifically, the new HTL-MOPSO combines the canonical PSO search with a teaching-learning-based optimization (TLBO) algorithm in order to promote the diversity and improve search ability. Also, CCS technique is developed to improve the diversity and spread of solutions when truncating the external elitism archive. The performance of HTL-MOPSO algorithm was tested on several well-known benchmarks problems and compared with other state-of-the-art MOO algorithms in respect of convergence and spread of final solutions to the true Pareto front. Also, the individual contributions made by the strategies of HTL-PSO and CCS are analyzed. Experimental results validate the effectiveness of HTL-MOPSO and demonstrate its superior ability to find solutions of better spread and diversity, while assuring a good convergence.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Elsevier. This is an author produced version of a paper subsequently published in Neurocomputing. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Multi-objective optimization; Particle swarm optimization; Teaching learning based optimization; Crowded sorting |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 09 Mar 2017 12:35 |
Last Modified: | 05 Oct 2017 03:30 |
Published Version: | https://doi.org/10.1016/j.neucom.2016.10.001 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.neucom.2016.10.001 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:113056 |
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