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Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm
The optimal scheduling of mine water is a multi-objective, multi-constraint, nonlinear, multi-stage combination of optimization problems, in view of the traditional solution methods with the increase in decision-making variable dimensions facing a large amount of computation, “dimensional disaster”...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315798/ https://www.ncbi.nlm.nih.gov/pubmed/35890936 http://dx.doi.org/10.3390/s22145256 |
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author | Yue, Yuangan Liu, Yang Bo, Lei Zhang, Zihang Yang, Hongwei Wang, Yiying |
author_facet | Yue, Yuangan Liu, Yang Bo, Lei Zhang, Zihang Yang, Hongwei Wang, Yiying |
author_sort | Yue, Yuangan |
collection | PubMed |
description | The optimal scheduling of mine water is a multi-objective, multi-constraint, nonlinear, multi-stage combination of optimization problems, in view of the traditional solution methods with the increase in decision-making variable dimensions facing a large amount of computation, “dimensional disaster” and other problems, the introduction of a new intelligent simulation algorithm—the Whale Optimization Algorithm to solve the optimal scheduling problem of mine water. Aiming at the problem that the Whale Optimization Algorithm itself is prone to local optimization and slow convergence, it has been improved by improving its own parameters and introducing the inertia weight of the particle swarm and has achieved more obvious results. According to the actual situation of Nalinhe No. 2 Mine, the mathematical model of multi-target optimization of mine water is established based on the function of reuse time and reuse cost of mine water as the target function, and the balance of supply and demand of mine water, the water quality requirements of water use points at all levels, the water quantity requirements of reservoirs and the priority of water supply as the constraints. The improved Whale Optimization Algorithm was used to search optimal solution, and the results showed that the adaptability value of the improved Whale Optimization Algorithm was significantly improved compared with before, of which 8.65% and 7.69% were increased in the heating season and non-heating season, and the rate of cost reduction was 46.80% and 36.92%, and the iteration efficiency was also significantly improved, which improved the decision-making efficiency of optimal scheduling and became more suitable for the actual scheduling needs of Nalinhe No. 2 mine. |
format | Online Article Text |
id | pubmed-9315798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93157982022-07-27 Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm Yue, Yuangan Liu, Yang Bo, Lei Zhang, Zihang Yang, Hongwei Wang, Yiying Sensors (Basel) Article The optimal scheduling of mine water is a multi-objective, multi-constraint, nonlinear, multi-stage combination of optimization problems, in view of the traditional solution methods with the increase in decision-making variable dimensions facing a large amount of computation, “dimensional disaster” and other problems, the introduction of a new intelligent simulation algorithm—the Whale Optimization Algorithm to solve the optimal scheduling problem of mine water. Aiming at the problem that the Whale Optimization Algorithm itself is prone to local optimization and slow convergence, it has been improved by improving its own parameters and introducing the inertia weight of the particle swarm and has achieved more obvious results. According to the actual situation of Nalinhe No. 2 Mine, the mathematical model of multi-target optimization of mine water is established based on the function of reuse time and reuse cost of mine water as the target function, and the balance of supply and demand of mine water, the water quality requirements of water use points at all levels, the water quantity requirements of reservoirs and the priority of water supply as the constraints. The improved Whale Optimization Algorithm was used to search optimal solution, and the results showed that the adaptability value of the improved Whale Optimization Algorithm was significantly improved compared with before, of which 8.65% and 7.69% were increased in the heating season and non-heating season, and the rate of cost reduction was 46.80% and 36.92%, and the iteration efficiency was also significantly improved, which improved the decision-making efficiency of optimal scheduling and became more suitable for the actual scheduling needs of Nalinhe No. 2 mine. MDPI 2022-07-14 /pmc/articles/PMC9315798/ /pubmed/35890936 http://dx.doi.org/10.3390/s22145256 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yue, Yuangan Liu, Yang Bo, Lei Zhang, Zihang Yang, Hongwei Wang, Yiying Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm |
title | Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm |
title_full | Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm |
title_fullStr | Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm |
title_full_unstemmed | Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm |
title_short | Optimal Reuse Design Scheduling of Mine Water Based on Improved Whale Algorithm |
title_sort | optimal reuse design scheduling of mine water based on improved whale algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315798/ https://www.ncbi.nlm.nih.gov/pubmed/35890936 http://dx.doi.org/10.3390/s22145256 |
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