A Mathematical Programming Model for Off-street Public Parking Facilities Location (Case Study: The Central District of Isfahan)

The increasing in population and unbalanced urban growth associated with massive use of private cars in metropolitan areas lead to traffic congestions. In order to decrease traffic congestion, it is necessary to bulid public parking facilities. However, finding the best location for such capital-intensive facilities which conveniently serve all citizens is a must. In this paper, using lo
The increasing population and unbalanced urban growth associated with massive use of private cars in metropolitan areas lead to traffic congestions. In order to decrease traffic congestion, it is necessary to build public parking facilities. However, finding the best location for such capital-intensive facilities which conveniently serve all citizens is unavoidable. In this paper, a multi-objective model is proposed using location theory. The objectives considered for the public off-street parking location problem include maximizing covered demand, minimizing walking distance between demand points and new parking facilities and decreasing related costs. Also, parking facilities covering distance were assumed uncertain and different types of parking were considered. Finally, relevant information and data required for implementing the proposed model were collected from two traffic zones in central business districts (CBD) of Isfahan. The ε-constraint method was used to solve the multi-objective model and the best points for building new off-street parking facilities were determined. The results were confirmed by urban transport experts.
cation theory a multi-objective model is proposed. The objectives were considered for the public off-street parking location problem include maximizing covered demand, minimizing walking distance between demand points and new parking facilities and decreasing related costs. Also parking facilities covering distance were assumed uncertain and different types of parking were considered. Finally, relevant information and data required for implementing the proposed model were gathered on two traffic zones in central business districts (CBD) of Isfahan. Then the ε-constraint method was used to solve the multi-objective model and the best points for building new off-street parking facilities were determined. These results were confirmed by urban transport experts.