Optimal Integrated Model for Feeder Transit Route Design and Frequency-Setting Problem with Stop Selection

Abstract

This study proposed a mathematical model for designing a feeder transit service for improving the service quality and accessibility of transportation hubs (such as airport and rail station). The proposed model featured an integrated framework, which simultaneously guided passengers to reach their nearest stops to get on and off the bus, designed routes to transport passengers from these selected pick-up stops to the transportation hubs, and calculated their departure frequencies. In particular, the maximum walking distance, the upper and lower limits of route frequencies, and the load factor rate of each route were fully accounted for in this study. The main objective of the proposed model was to simultaneously minimize the total walking, riding time, and waiting time of all passengers. As this study explored an NP-hard problem, a two-stage genetic algorithm combining the Dijkstra search method was further developed to yield metaoptimal solutions to the model within an acceptable time. Finally, a test instance in Chongqing City, China, demonstrated that the proposed model was an effective tool to generate a pedestrian, route, and operation plan; it reduced the total travel time, compared with the traditional model.

Evaluating the Quality of Service of Bus Performance in Johor Bahru

“…Globalisation and technology had led towards industrial revolution (IR) 4.0, in which every angle of the daily life is connected with Internet of Things (IOT) [34]. The government should assist key players in bus industries to develop and implement a new technology in bus services to improve its quality of for bus performance, such as actual time bus services [34], designing a significant feeder transit [32], optimisation of bus schedules [31], and systematic departure and arrival of buses [28]. By adapting this technology, trustworthiness and passenger and user perceptions towards bus services can also be increased as operators can deliver services of good quality [24].…”

A survey on demand-responsive public bus systems

“…Unlike Sun et al (2019a), Wei et al (2020) study a stop-based feeder system, without a door-to-door service. This system assigns passengers to a bus stop based on their real-time locations during peak hours.…”

A column generation algorithm for the demand‐responsive feeder service with mandatory and optional, clustered bus‐stops

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