ساجده نعمتي نقلبري

Today, weather forecasting plays a critical role in human life to prevent massive damage to human societies, urban infrastructure, and industries. Weather stations as facilities on land or sea have tools for observing the state of the earth's atmosphere and information for studying weather and climate. Therefore, it is vital finding the best location to establish weather stations monitoring temperature, air pressure, humidity, precipitation and wind speed. In order to investigate this problem, this paper proposes an integrated hierarchical maximum covering bi-objective mixed integer linear programming model for weather stations network design. There are two objectives: locating weather stations in the best possible locations and finding the least number of weather stations implies the minimum cost of locating weather station means fixed cost of constructing weather station facility and preparing station land according to each state and also operational costs (supplying measuring devices). In this mathematical model, weather stations are geographically classified into two levels: local and provincial and also a central station in Tehran. The distance between stations varies depending on the level of the stations. There is an extended coverage radius for higher level stations, i.e. provincial which give services to lower level stations, i.e. local in the coverage radius of provincial. Moreover, the model allocates (thermometer, barometer, hygrometer, rain gauge, and anemometer) required depending on the stations levels by considering measuring devices accuracy which differs according to its type; automatic or manual. In the first objective function consider the efficiency of possible points as weights using data envelopment analysis method (DEA) to study the value of appropriate attributes affecting the quality of a weather station location and the latter as the second objective function. The DEAs model Inputs are land slope and distance to geological faults, and outputs include distance to the airport, industrial centers, and population. In the following, to solve the proposed model, the ε-constraint approach is used to transform a multi-objective into a single-objective problem, afterward, the Lagrangian relaxation approach is applied to effectively solve the problem in timely fashion. Finally, the application of the model has been eva‎luated through a real case study in Iran and several managerial insights have been also presented.

ايستگاه هواشناسي , پارامترهاي هواشناسي , مكان‌يابي با پوشش حداكثري , تحليل پوششي داده¬ , روش اپسيلون محدوديت , لاگرانژ

Weather station , Meteorological parameters , Hierarchical maximum covering , Data envelopment analysis , ɛ-constraint method , Lagrangian relaxation approach

Sajedeh Nemati

Saeed Yaghoubi