The Assessment of BCO algorithm's performance in temporary housing problem after earthquake

The temporary housing problem plays essential role in disaster management since its usage would significantly reduce the number of casualties (human and financial tolls). Different factors such as minimizing the transportation of people and homogeneous distribution of population based on safe areas’ capacity should be simultaneously optimized in order to achieve the best solution for temporary housing problem. Two objective functions were defined and their weight was estimated using AHP, then a single objective function was produced using weighted average of the initial objective functions. The objective of this research is to assess the functionality of Bees algorithm in the process of optimizing the objective function. BCO is inspired by the natural foraging behavior of honey bees to find the optimal solution. In order to calibrate the aforementioned algorithm a batch of simulated data has been used and then in order to assess the functionality of the calibrated algorithm the real data of the 7th district of Tehran has been used. Then a repeatability test has been conducted in order to assess the accuracy of the algorithm. The results showed that by using this algorithm the assignment of population to the safe areas is facilitated.