Personalised and Coordinated Demand-Responsive Feeder Transit Service Design: A Genetic Algorithms Approach

Bo Sun, Ming Wei, Chunfeng Yang, Zhihuo Xu and Han Wang
Additional contact information
Bo Sun: School of Transportation, Nantong University, Nantong 226019, China
Ming Wei: School of Transportation, Nantong University, Nantong 226019, China
Chunfeng Yang: College of Civil Engineering, Hebei University of Technology, Tianjin 300401, China
Zhihuo Xu: School of Transportation, Nantong University, Nantong 226019, China
Han Wang: School of Transportation, Nantong University, Nantong 226019, China

Future Internet, 2018, vol. 10, issue 7, 1-14

Abstract: The purpose of this work is to create an efficient optimization framework for demand-responsive feeder transit services to assign vehicles to cover all pickup locations to transport passengers to a rail station. The proposed methodology features passengers placing a personalized travel order involving the subway schedule chosen by passengers and windows of service time, etc. Moreover, synchronous transfer between the shuttle and feeder bus is fully accounted for in the problem. A mixed-integer linear programming model is formulated to minimize the total travel time for all passengers, which consists of ride-time for vehicles from the pickup locations to the rail station and wait-time for passengers taking the subway beforehand. Different from conventional methods, the proposed model benefits from using a real distribution of passenger demand aggregated from cellular data and travel time or the distance matrix obtained from an open GIS tool. A distributed genetic algorithm is further designed to obtain meta-optimal solutions in a reasonable amount of time. When applied to design a feeder bus system in Nanjing City, China, case study results reveal that the total travel time of the proposed model was reduced by 2.46% compared to the traditional model. Sensitivity analyses were also further performed to investigate the impact of the number of vehicles on the output. Finally, the difference in results of Cplex, standard GA, and the proposed algorithm were compared to prove the validity of the algorithm.

Keywords: DRC transit system; synchronous transfer of rail transit; personalized travel; heuristic algorithm (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1999-5903/10/7/61/pdf (application/pdf)
https://www.mdpi.com/1999-5903/10/7/61/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:10:y:2018:i:7:p:61-:d:155497

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().