Khodakaram Salimifard
A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs
Salimifard, Khodakaram; Li, Jingpeng; Mohammadi, Davood; Moghdani, Reza
Authors
Jingpeng Li
Davood Mohammadi
Reza Moghdani
Abstract
Parallel machine scheduling is one of the most common studied problems in recent years, however, this classic optimization problem has to achieve two conflicting objectives, i.e. minimizing the total tardiness and minimizing the total wastes, if the scheduling is done in the context of plastic injection industry where jobs are splitting and molds are important constraints. This paper proposes a mathematical model for scheduling parallel machines with splitting jobs and resource constraints. Two minimization objectives - the total tardiness and the number of waste - are considered, simultaneously. The obtained model is a bi-objective integer linear programming model that is shown to be of NP-hard class optimization problems. In this paper, a novel Multi-Objective Volleyball Premier League (MOVPL) algorithm is presented for solving the aforementioned problem. This algorithm uses the crowding distance concept used in NSGA-II as an extension of the Volleyball Premier League (VPL) that we recently introduced. Furthermore, the results are compared with six multi-objective metaheuristic algorithms of MOPSO, NSGA-II, MOGWO, MOALO, MOEA/D, and SPEA2. Using five standard metrics and ten test problems, the performance of the Pareto-based algorithms was investigated. The results demonstrate that in general, the proposed algorithm has supremacy than the other four algorithms.
Citation
Salimifard, K., Li, J., Mohammadi, D., & Moghdani, R. (2021). A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs. Applied Intelligence, 51(7), 4143-4161. https://doi.org/10.1007/s10489-020-02027-1
| Journal Article Type | Article |
|---|---|
| Acceptance Date | Oct 16, 2020 |
| Online Publication Date | Dec 8, 2020 |
| Publication Date | 2021-07 |
| Deposit Date | Feb 22, 2023 |
| Publicly Available Date | Mar 2, 2023 |
| Journal | Applied Intelligence |
| Print ISSN | 0924-669X |
| Electronic ISSN | 1573-7497 |
| Publisher | Springer (part of Springer Nature) |
| Peer Reviewed | Peer Reviewed |
| Volume | 51 |
| Issue | 7 |
| Pages | 4143-4161 |
| DOI | https://doi.org/10.1007/s10489-020-02027-1 |
| Keywords | Parallel machine scheduling; Splitting jobs; Wastes; Total tardiness; Multi-objective optimisation; Volleyball premier league |
| Public URL | https://hull-repository.worktribe.com/output/4210285 |
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Copyright Statement
© The Author(s) 2020.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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