Garage Location Selection for Public Transportation System in Istanbul

Conclusion

Istanbul is a growing city and the land use is very important in terms of the city master plans. Considering this reality, we determined probable bus garage locations by taking the opinions of IETT authorities. The main contribution to the literature is applying fuzzy AD and weighted fuzzy AD integrating with fuzzy AHP to select the best alternative garage location for the biggest city in Turkey, Istanbul.

The aim of using AD is taking into account the design ranges for all attributes. Besides, making the evaluation by using linguistic terms and transforming them into fuzzy numbers is an easier way for decision makers. It helps the decision maker to select the most appropriate alternative that is suitable with his/her design features. This is the strength of the proposed method over the existing ones. AD approach uses design ranges for each criterion, determined by the designer. Thus, the alternatives, which ensure the design ranges, are selected in AD approach. However, other multicriteria methods select the alternatives that meet the criteria at their best levels. The AD approach also differs from many other existing methods from the point of the rejection of an alternative when it does not meet the design range of any criterion.

By taking these advantages, fuzzy AD is applied and Arnavutköy for European Side and Sultanbeyli for Asian Side of Istanbul are selected. In weighted fuzzy AD the same garage locations are selected. Even if the obtained results are similar, the weights of the criteria generally very important in terms of the decision makers. In scenario analysis, effects of the criteria weights on the results are depicted.

After manual calculations, we solved our problem by ADSolver which solves the problem directly in terms of the user. This computer program is very useful for the decision makers and it increases the applicability of the approach. In future studies, the combined transportation systems in different modes can be adapted to the problem. The effect of this enhancement will be an increase in the number of criteria. Under this circumstance solving the problem by ADSolver will be more significant.