Abstract
Nowadays, authorities of large cities in the world implement bus rapid transit (BRT) services to alleviate traffic problems caused by the significant development of urban areas. Therefore, a controller is required to control and dispatche buses in such BRT systems.. However, controllers are facing new challenges due to the inherent uncertainties of passenger parameters such as arrival times, demands, alighting fraction as well as running time of vehicles between stops. Such uncertainties may significantly increase the operational cost and the inefficiencies of BRT services. In this paper, we focus on the controller’s perspective and propose a stochastic mixed-integer nonlinear programming (MINLP) model for BRT scheduling to find the optimal departure time of buses under uncertainty. The objective function of the model consists of passenger waiting and traveling time and aims to minimize total time related to passengers at any stop. From the modeling perspective, we propose a new method to generate scenarios for the proposed stochastic MINLP model. Furthermore, from the computational point of view, we implement an outer approximation algorithm to solve the proposed stochastic MINLP model and demonstrate the merits of the proposed solution method in the numerical results. This paper accurately reflect the complexity of BRT scheduling problem and is the first study, to the best of our knowledge, that presents and solves a mixed-integer nonlinear programming model for BRT scheduling.
Highlights
Due to increasing environmental pollution and traffic congestion, many strategies on giving some priority to the urban transportation system development have recently been formed
We propose a stochastic mixed-integer nonlinear programming (MINLP) program that more accurately models the characteristics of bus rapid transit (BRT) scheduling problems, especially the cost function
For brevity and simplicity in notations, we show the steps of the outer approximation (OA) algorithm on the general problem (20a) in matrix form
Summary
Due to increasing environmental pollution and traffic congestion, many strategies on giving some priority to the urban transportation system development have recently been formed. Bus transit planning captured increasing attention among researchers. A wide area of research is covered by public transit planning and prevention which is divided into a sequence of several distinguished steps, namely (1) route design, (2) setting of frequency, (3) timetabling, (4) vehicle scheduling, (5) crew scheduling, and (6) transportation system protection and resilience [1,2,3]. In cities around the world, bus rapid transit (BRT) helps people move more reliably and quickly due to having less congestion with usual traffic because of their dedicated lanes and stations [4]. It has been recently shown that BRT systems have many advantages including
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