عنوان مقاله [English]
Hospitals are one of the most important centers of medical service. At the time of the occurrence of natural and abnormal disasters, the demand for these centers may increase and some of these hospitals will be damaged and lose their functionality. On the other hand, in order to protect the lives of the injured, the distance and time of their transfer to hospitals are of particular importance.
The proposed problem addressed simultaneously the crisis and normal conditions and tried to determine the location of hospitals in such a way that with limited resources in hand and the normal capacity and extra that can be used in times of crisis, the minimum distances Have Taking into account the decisions of the hardening of existing hospitals and the location of new hospitals simultaneously, post-abandonment distances are reduced compared to when the location is taken regardless of disability and rehabilitation, and this can be an effective step in crisis management. The capacity of hospitals in normal conditions and in the event of a crisis is limited and considering this in the model gives more realistic results.
In this research, the problem of locating new hospitals and hardening a number of existing hospitals with limited available budget has been discussed. First, the potential locations to build a hospital are specified. Then, using the proposed mathematical model, the optimal locations for the construction of new hospitals were determined, as well as decisions regarding the hardening of a number of existing hospitals. In order to solve the model due to its bi-objective function, the Augmented Epsilon Constraint Method II is used. To evaluate the validity of the model, a case study was carried out based on demographic and geographical information of Yazd city. Regarding the possibility of applying the model to large-scale applications and operating issues as well as NP-hardness of the model, an innovative multi-objective two-phase algorithm is proposed and evaluated based on some numerical examples.