An Approach to the Joint Rapid and Slow Transit Network Design Problem

TL;DR

This paper presents an integrated mathematical model for designing rapid transit lines alongside redesigning slow transit networks, aiming to maximize demand coverage and improve efficiency in urban transportation planning.

Contribution

It introduces a novel combined optimization approach using an improved Benders decomposition for simultaneous transit network design and redesign.

Findings

Model effectively captures the joint design problem.

Computational experiments demonstrate improved demand coverage.

Partial decomposition accelerates solution process.

Abstract

The increase in congestion in surface traffic, airborne pollution, and other environmental issues have motivated the transit authorities to promote public transit worldwide. In big cities and large metropolitan areas, adding new rapid transit lines attracts more commuters to the public system, as they frequently allow saving travel time as compared to the private mode (car) that faces high congestion. In addition, the travel time has less variability with respect to preset schedules, and rapid lines are more efficient than slow modes operated by buses. When a new rapid transit line is constructed, it partially replaces the traffic of existing slow transit lines. As a consequence, some of the slow-mode lines have to be either canceled or their routes modified to collaborate properly with the new rapid transit line. This process is usually carried out in a sequential way, thus leading to suboptimal solutions. In this paper, we consider an integrated model for simultaneously designing rapid and redesigning slow networks. The aim of the model is community-oriented, that is, to maximize the demand covered (or captured) by both modes. We present a mathematical programming formulation that is solved by using a specially improved Benders decomposition. For this purpose, we include a partial decomposition to speed up the computation. The computational experiments are done on a case study based on real data obtained from a survey of mobility among transportation zones in the city of Seville.