implementing solution algorithms for a bi-level optimization to the emergency warehouse location-allocation problem

The aim of this paper was to develop a binary bi-level optimization model for the emergency warehouse location-allocation problem in terms of national and regional levels. this type of modeling is suitable for countries where the design of the disaster emergency network is decentralized. the upper-level decision-maker makes a decision regarding the location and allocation of national warehouses through considering the location of regional warehouses and allocating them to the demand cities. each regional warehouse can provide a service for the demand cities within a specified distance threshold, ultimately affecting the efficiency of the solution algorithms. the optimization model parameters were calculated in terms of the real data in iran. to solve the small size problem, an exact method was proposed from the explicit complete enumeration. due to the complexity of the model with the large size, two innovative hybrid genetic algorithms, namely hg-es-1 and hg-es-2, were suggested. the results obtained from solving the problems showed that the hg-es-1 algorithm outperformed hg-es-2. the findings further indicated the proper functioning of the solution approaches.