Optimizing Mine Ventilation Systems: An Advanced Mixed-Integer Linear Programming Model
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| Udgivet i: | Mathematics vol. 13, no. 18 (2025), p. 2906-2925 |
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MDPI AG
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| Online adgang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2227-7390 | ||
| 024 | 7 | |a 10.3390/math13182906 |2 doi | |
| 035 | |a 3254583171 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231533 |2 nlm | ||
| 100 | 1 | |a Zhong Deyun |u State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, China University of Mining and Technology, No. 1 University Road, Xuzhou 221116, China; deyun_zhong@csu.edu.cn | |
| 245 | 1 | |a Optimizing Mine Ventilation Systems: An Advanced Mixed-Integer Linear Programming Model | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a In the underground mine ventilation area, the absence of robust solutions for nonlinear programming models has impeded progress for decades. To overcome the enduring difficulty of solving nonlinear optimization models for mine ventilation optimization, a major technical bottleneck, we first develop an advanced linear optimization technique. This method transforms the nonlinear ventilation optimization and regulation model into a linear control model, avoiding the limitation of difficulty in solving the nonlinear mathematical model. The linear strategy opens up a new solution idea for the nonlinear calculation of the mine ventilation optimization and regulation. Furthermore, this study introduces evaluation metrics for ventilation scheme quality, including minimal energy consumption, fewest adjustment points, and optimal placement of these points, enhancing flexibility in ventilation network optimization. By analyzing the ventilation model control objectives and constraints, we formulated a linear optimization model and developed a multi-objective mixed-integer programming model for ventilation network optimization. This paper constructs and verifies a calculation example model for mine ventilation optimization, assessing its reliability based on airflow distribution calculations. | |
| 610 | 4 | |a China University of Mining & Technology | |
| 651 | 4 | |a China | |
| 653 | |a Air flow | ||
| 653 | |a Mines | ||
| 653 | |a Mine ventilation | ||
| 653 | |a Linear programming | ||
| 653 | |a Coal mining | ||
| 653 | |a Integer programming | ||
| 653 | |a Underground mines | ||
| 653 | |a Mathematical models | ||
| 653 | |a Network management systems | ||
| 653 | |a Optimization | ||
| 653 | |a Linear control | ||
| 653 | |a Variables | ||
| 653 | |a Pressure distribution | ||
| 653 | |a Methods | ||
| 653 | |a Algorithms | ||
| 653 | |a Mixed integer | ||
| 653 | |a Objectives | ||
| 653 | |a Energy consumption | ||
| 653 | |a Nonlinear programming | ||
| 653 | |a Optimization models | ||
| 700 | 1 | |a Wen Lixue |u School of Resources and Safety Engineering, Central South University, Changsha 410083, China; 225512108@csu.edu.cn (L.W.); 225512106@csu.edu.cn (Y.L.) | |
| 700 | 1 | |a Liu, Yulong |u School of Resources and Safety Engineering, Central South University, Changsha 410083, China; 225512108@csu.edu.cn (L.W.); 225512106@csu.edu.cn (Y.L.) | |
| 700 | 1 | |a Wu Zhaohao |u School of Resources and Safety Engineering, Central South University, Changsha 410083, China; 225512108@csu.edu.cn (L.W.); 225512106@csu.edu.cn (Y.L.) | |
| 700 | 1 | |a Wang Liguan |u Changsha DIMINE Co., Ltd., Changsha 410221, China; liguan_wang@csu.edu.cn | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 18 (2025), p. 2906-2925 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3254583171/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3254583171/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3254583171/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |