Using Tabu Search Algorithm and Geospatial Information System for Managing of the Relief and Rescue Teams

Every year, natural disasters have devastated many victims around the world. The earthquake is one of the above natural phenomena that Iran is vulnerable to earthquake events due to being seated in earthquake zones of the world and possessing a relatively high population. Various factors affect the damage caused by earthquakes. Among these factors, we can indicate the time and severity of the earthquake, the strength of the structures, the type of use of the structures and the way of relief after the earthquake. Therefore, studying in these areas, and in particular, the promotion of earthquake relief and rescue, can have a positive effect on the reduction of human and financial losses. In this regard, during the present research, the duties and activities of the rescue and rescue forces were investigated at the time of the earthquake. Also, due to the impossibility of placing in post-earthquake conditions at the time of conducting the present research, an assumed earthquake in a similar study area The amount of damages to the region has been calculated. Considering the damage inflicted on the study area, the present research determines the priorities of the relief and rescue activities, and then the relief and rescue forces will be allocated to the selected activities with consideration of their abilities and specialties. To carry out the research, simulation of relief and rescue operations is considered for a group of operations with six rescue teams of eight. Also, due to the objective of this research, which is the optimal allocation of relief and rescue teams to the area of ​​earthquake occurrence, for the optimal allocation of relief and rescue forces to the activities of the region, the spatial information system and the tabu search algorithm have been used and similar The aforementioned tools such as earthquake events and their damage estimation, rescue teams, and descriptive information are introduced into this system. Also, a function under the title of income has been introduced in this study, which serves as a target function in the tabu search algorithm. It is considered and optimized. Finally, the results from the implementation of the proposed algorithm in this study have shown that the use of the tabu search algorithm to optimize allocation of relief and rescue teams after an earthquake, then when this algorithm is not used to optimize the target function, and Also, earthquake simulation, teams and activities are not performed according to the model presented in this study, improvement of 1.41 fold. Given the fact that the structure of relief and rescue teams has been done according to reality, the use of this algorithm to optimize the simulations of this research as well as the implementation of the scientific and practical structure of the activities and rescue teams will be a modern and efficient way to improve the quality of post-earthquake relief and rescue.