Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/104192
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | en_US |
| dc.creator | Fu, X | en_US |
| dc.creator | Chan, FTS | en_US |
| dc.creator | Niu, B | en_US |
| dc.creator | Chung, NSH | en_US |
| dc.creator | Qu, T | en_US |
| dc.date.accessioned | 2024-02-05T08:47:01Z | - |
| dc.date.available | 2024-02-05T08:47:01Z | - |
| dc.identifier.issn | 2210-6502 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/104192 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier BV | en_US |
| dc.rights | © 2019 Published by Elsevier B.V. | en_US |
| dc.rights | © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
| dc.rights | The following publication Fu, X., Chan, F. T. S., Niu, B., Chung, N. S. H., & Qu, T. (2019). A three-level particle swarm optimization with variable neighbourhood search algorithm for the production scheduling problem with mould maintenance. Swarm and Evolutionary Computation, 50, 100572 is available at https://doi.org/10.1016/j.swevo.2019.100572. | en_US |
| dc.subject | Machine maintenance | en_US |
| dc.subject | Mould maintenance | en_US |
| dc.subject | Production scheduling | en_US |
| dc.subject | Three-level particle swarm optimization | en_US |
| dc.subject | Variable neighbourhood search | en_US |
| dc.title | A three-level particle swarm optimization with variable neighbourhood search algorithm for the production scheduling problem with mould maintenance | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 50 | en_US |
| dc.identifier.doi | 10.1016/j.swevo.2019.100572 | en_US |
| dcterms.abstract | To improve the reliability of production systems in the plastics industry, researchers are now taking mould maintenance into consideration, besides machine maintenance, in the production scheduling problem. Different strategies and approaches have been proposed to solve the production scheduling with mould maintenance (PS-MM) problem. However, it remains a challenge to provide a satisfactory solution. In this research, a new hybrid metaheuristic algorithm (TLPSO-VNS algorithm) is proposed, which is a combination of the three-level particle swarm optimization (TLPSO) algorithm devised in this study and variable neighbourhood search (VNS). Differing from the joint scheduling strategies used in existing research, this study divides the integrated problem into three sub-problems and solves them through three interrelated PSOs named TLPSO. Then, the solutions obtained by TLPSO are enhanced by VNS. The key characteristics of TLPSO and VNS are employed simultaneously to achieve superior solutions in solving the addressed optimization problem. In the proposed hybrid algorithm, the TLPSO performs a global search whereas the VNS has a local search role. These two techniques complement each other to enhance the search diversification and intensification. Numerical experiments on a variety of simulated scenarios show the efficiency and effectiveness of the proposed algorithm by comparing it with other algorithms. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Swarm and evolutionary computation, Nov. 2019, v. 50, 100572 | en_US |
| dcterms.isPartOf | Swarm and evolutionary computation | en_US |
| dcterms.issued | 2019-11 | - |
| dc.identifier.scopus | 2-s2.0-85072522341 | - |
| dc.identifier.eissn | 2210-6510 | en_US |
| dc.identifier.artn | 100572 | en_US |
| dc.description.validate | 202402 bcch | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | ISE-0399 | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 23026358 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Fu_Three-Level_Particle_Swarm.pdf | Pre-Published version | 2.23 MB | Adobe PDF | View/Open |
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