using genetic algorithm for optimizing multiobjective locatio-allocation in gis environment (casestudy: firestations in district 11 of tehran city)

In this article، multiobjective location-allocation in GIS environment to optimizing firestations in district 11 of Tehran city with genetic algorithm is important. Objectives of this article are: 1-minimize distance between firestations and demands 2- minimize arriving time to demands from firestations 3- maximize firestations covering in distict 11 of Tehran city. Location-Allocation is a combinatorial optimization problem that knowns as NP-hard beacause this problem has computional complexity. So traditional exact methods cannot solve multiobjectivelocation-allocation problem efficiently. To solving this location-allocation problem isusedgenetic algorithmmetaheuristic method. In this multiobjective genetic algorithm (MOLA)، to assess the impact of each objective، first the model is implemented as single objective to each function and the results compared. Second، the multiobjective model is used with priority weight vector. The results indicate the model can successfully provide optimum locations for firestations with capacity criteria. Then، this study use from dynamic weighting scheme. In this case a random weight vector is assing to each soloution in each iteration and produce set of non-dominated soloutions. These soloutions act as a candidate pool which decision maker may choose soloutions according to their preferences or determinent criteria.