Journal of Industrial Engineering and Management Studies

Abstract Fast growth of motorized transportation infrastructures in the cities is a consequence of the urbanization process. Despite the undeniable benefits of the developments, some unwelcome social-environmental damages have been occurred. On top of the list, the movements of the pedestrians and their participation in social activities have dramatically reduced as a result of the vehicles dominancy. Pedestrianization and walking-friendly schemes are the key answer to preserve the valuable element of the urban lifestyle. This need motivated the researchers to study and propose mathematical methods to model the dynamics and behavior of the pedestrians in response to their surroundings. However, most of the models in the literature are suitable for limited small-size area and cannot be applied for a large scale urban zone. In this paper, a fuzzy macroscopic pedestrian assignment model is proposed which is applicable for a large scale network and useful for urban master plans as a decision making framework. In addition, a bi-level mixed integer programming model is presented to optimize the pedestrian walking network via selecting some projects on the network, considering the behavior of the pedestrians. Finally, the problem is solved for a large scale pedestrian network in the city of Tehran. The results show the efficiency of the algorithm where spending half of the maximum possible cost has led to a welfare gain of 82.6 percent. The problem was efficiently solved within 12.5 days which is fairly acceptable for the strategic planning of such a large scale network. The numerical results verify the necessity of the model for urban master plan horizon.

Abstract Motorized transportation systems in the urban areas witnessed huge developments in the infrastructures thanks to the advances in various aspects of technology. This urbanization revolution has its own pros and cons. The resulting dominance of vehicles has limited the presence of people in public places and their participation in social activities, threatening the human based lifestyle of the cities. Historic districts are of most affected areas which withstand the unwanted consequences of such an experience. These areas play a substantial role in urban activities by providing great social activity and walking zones for pedestrians. Hence, in recent years, urban management has paid attention to this endanger regions in order to sustain and enhance their properties by introducing some pedestrianization plan as urban regeneration policies. To design an effective plan, it is necessary to figure out how people behave in response to their environment. Pedestrian modeling is the key to the problem and is studied in the past few decades, mostly in microscopic scale. In addition, a logical decision-making process is required to choose the option with the best outcome in this complex system, considering financial limits of strategic urban planning. In this paper, a macroscopic multi-class user equilibrium pedestrian assignment algorithm is proposed to anticipate the route choice behavior of the pedestrians in a network, and a decision making platform for the pedestrian network design is presented using bi-level mathematical mixed-integer programming and genetic algorithm. The presented model determines the best possible projects to be implemented on the network, considering the constraints of the historic districts. The model brings forward an intelligent framework to help the urban planners in spending the minimum cost, while maximizing some predefined objectives. The proposed method is applied to solve the problem in a test network and in a real case scenario for the historic district of the city of Tehran. The results prove the validity and the efficiency of the algorithm.