An integrated optimization approach for weather stations network design: a case study
Accurate and reliable weather forecasting plays a crucial role in supporting decision-making and resource management across multiple sectors, particularly in agriculture and transportation. To enhance forecasting capabilities, this study develops an integrated and optimized meteorological station ne...
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| Published in: | Theoretical and applied climatology Vol. 156; no. 6; p. 334 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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01.06.2025
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| ISSN: | 0177-798X, 1434-4483 |
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| Abstract | Accurate and reliable weather forecasting plays a crucial role in supporting decision-making and resource management across multiple sectors, particularly in agriculture and transportation. To enhance forecasting capabilities, this study develops an integrated and optimized meteorological station network that simultaneously addresses optimal placement and comprehensive weather parameter monitoring and managerial aspects. In so doing, this paper develops a bi-objective integer linear programming model for designing a network of meteorological centers, which incorporates not only atmospheric conditions, but also integrates efficiency assessment of weather stations according to their locations, prevailing climatic conditions and need for different stations for each climate, climatic variations across provinces and managerial aspects, and device (sensor) allocation to station in order to measure required weather parameters. As this paper aims to contribute in providing a thorough framework and cover most of the weather station related decisions and considerations, the decision-making process is carried out through a two phase procedure. First phase is the efficiency assessment phase, which potential locations of stations are valuated using Data Envelopment Analysis (DEA) based on factors such as terrain slope, population, and distance from airports, fault lines, and industrial centers. A bi-objective mathematical optimization model which covers the other related considerations and decisions, is developed in second phase. This model balances system efficiency with cost considerations as the objectives beside providing the integrated station network. Due to model complexity, an ε-constrained method converts it into a single-objective form, and Lagrangian relaxation ensures scalability. Finally, to demonstrate the practical applicability of this model, a case study from Iran is presented. |
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| AbstractList | Accurate and reliable weather forecasting plays a crucial role in supporting decision-making and resource management across multiple sectors, particularly in agriculture and transportation. To enhance forecasting capabilities, this study develops an integrated and optimized meteorological station network that simultaneously addresses optimal placement and comprehensive weather parameter monitoring and managerial aspects. In so doing, this paper develops a bi-objective integer linear programming model for designing a network of meteorological centers, which incorporates not only atmospheric conditions, but also integrates efficiency assessment of weather stations according to their locations, prevailing climatic conditions and need for different stations for each climate, climatic variations across provinces and managerial aspects, and device (sensor) allocation to station in order to measure required weather parameters. As this paper aims to contribute in providing a thorough framework and cover most of the weather station related decisions and considerations, the decision-making process is carried out through a two phase procedure. First phase is the efficiency assessment phase, which potential locations of stations are valuated using Data Envelopment Analysis (DEA) based on factors such as terrain slope, population, and distance from airports, fault lines, and industrial centers. A bi-objective mathematical optimization model which covers the other related considerations and decisions, is developed in second phase. This model balances system efficiency with cost considerations as the objectives beside providing the integrated station network. Due to model complexity, an ε-constrained method converts it into a single-objective form, and Lagrangian relaxation ensures scalability. Finally, to demonstrate the practical applicability of this model, a case study from Iran is presented. Accurate and reliable weather forecasting plays a crucial role in supporting decision-making and resource management across multiple sectors, particularly in agriculture and transportation. To enhance forecasting capabilities, this study develops an integrated and optimized meteorological station network that simultaneously addresses optimal placement and comprehensive weather parameter monitoring and managerial aspects. In so doing, this paper develops a bi-objective integer linear programming model for designing a network of meteorological centers, which incorporates not only atmospheric conditions, but also integrates efficiency assessment of weather stations according to their locations, prevailing climatic conditions and need for different stations for each climate, climatic variations across provinces and managerial aspects, and device (sensor) allocation to station in order to measure required weather parameters. As this paper aims to contribute in providing a thorough framework and cover most of the weather station related decisions and considerations, the decision-making process is carried out through a two phase procedure. First phase is the efficiency assessment phase, which potential locations of stations are valuated using Data Envelopment Analysis (DEA) based on factors such as terrain slope, population, and distance from airports, fault lines, and industrial centers. A bi-objective mathematical optimization model which covers the other related considerations and decisions, is developed in second phase. This model balances system efficiency with cost considerations as the objectives beside providing the integrated station network. Due to model complexity, an ε-constrained method converts it into a single-objective form, and Lagrangian relaxation ensures scalability. Finally, to demonstrate the practical applicability of this model, a case study from Iran is presented. |
| ArticleNumber | 334 |
| Author | Sadeghi, Mohammad Arefi, Sara Yaghoubi, Saeed Nemati, Sajedeh |
| Author_xml | – sequence: 1 givenname: Mohammad surname: Sadeghi fullname: Sadeghi, Mohammad organization: School of Industrial Engineering, Iran University of Science and Technology – sequence: 2 givenname: Saeed surname: Yaghoubi fullname: Yaghoubi, Saeed email: yaghoubi@iust.ac.ir organization: School of Industrial Engineering, Iran University of Science and Technology – sequence: 3 givenname: Sajedeh surname: Nemati fullname: Nemati, Sajedeh organization: School of Industrial Engineering, Iran University of Science and Technology – sequence: 4 givenname: Sara surname: Arefi fullname: Arefi, Sara organization: School of Industrial Engineering, Iran University of Science and Technology |
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| Title | An integrated optimization approach for weather stations network design: a case study |
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