Multi-Step Heuristic Method for Bus Terminal Location Problem

Abstract

Bus terminals are one of the main facilities that have a key role in the collection and distribution of passengers within an urban transportation network. The location of a bus terminal strongly affects its performance. Owing to the increasing demand, it is sometimes necessary to add a new bus terminal to the existing urban bus network. Finding a proper location, however, is a challenge that is influenced by different transportation and socio-economic considerations, which in turn affects the surrounding land-use and traffic patterns. In this paper, a new multi-step heuristic method is proposed for the bus terminal location problem to identify a new bus terminal location based on the existing network as well as other transportation considerations and constraints. This is achieved by identifying the existing bus stops that have the greatest potential to be turned into a bus terminal. Other factors taken into consideration are the locations of the existing bus terminals, adjacent land-use, construction costs, node connectivity, and system accessibility. Owing to the multi-objective nature of the problem, a goal programming approach is used to formulate the objective function. To evaluate the proposed model, it was applied to the city of Shiraz in Iran. The results show that the model can provide acceptable and reliable outcomes.

Optimization Method for Conventional Bus Stop Placement and the Bus Line Network Based on the Voronoi Diagram

“…Zhang [9] studied the impact of road space allocation on bus departure frequency and other operating conditions, and proposed the placement of bus demand-response stations and corresponding departure frequency under different road space conditions. Zamanian and Peiravian [10] proposed a new multi-step heuristic location method based on the existing network and other traffic factors, including the location of existing bus stops, adjacent land use, construction cost, node connectivity and system accessibility. Roy and Basu [11] studied the infrastructure of pedestrian transfer space between bus stops and between rail transit stops and bus stops; they identified the area by using a two-dimensional fuzzy c-means algorithm, and then studied the service level of passenger-pedestrian transfer.…”

“…The goal of this study is to reasonably adjust the existing conventional bus line network structure, enhance the competitiveness of bus travel and attract more passengers to choose bus travel. Therefore, this study takes Equations ( 7)- (10) as the objective function and weights the four parameters to find the optimal solution. Since Equations ( 7) and ( 9) seek the maximum and Equations ( 8) and (10) seek the minimum, this study takes the reciprocal of Equations ( 7) and ( 9) to make its optimization direction consistent.…”

“…Therefore, this study takes Equations ( 7)- (10) as the objective function and weights the four parameters to find the optimal solution. Since Equations ( 7) and ( 9) seek the maximum and Equations ( 8) and (10) seek the minimum, this study takes the reciprocal of Equations ( 7) and ( 9) to make its optimization direction consistent.…”