Using Similated Annealing Algorithm for Optimizing Multi objective Location-Allocation Problems in GIS Environment (Case Study: Firestations in District 11 of Tehran)

Introduction and Objective:

In this article, multiobjective location–allocation in GIS environment tooptimizing the location and allocation offirestations in district 11 of Tehran city 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.

Location-Allocation is a combinatorial optimization problem and because computing complexity those known as NP-hard. So,traditional exact method cannot solve complex Location-Allocation problem with multicriteria. To solve thisLocation-Allocation problem is used metaheuristicSimilated Annealingalgorithm.

This model findthe optimal location of firestations such that this firestations meet the demands Excellency.

In this multiobjective genetic model, to assess the impact of each objective, first the model is implemented as single objective to each function. 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 soloutionin 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.