Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

New heuristic and evolutionary operators for the multi-objective urban transit routing problem

Mumford, Christine Lesley ORCID: https://orcid.org/0000-0002-4514-0272 2013. New heuristic and evolutionary operators for the multi-objective urban transit routing problem. Presented at: 2013 IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico, 20-23 June 2013. Evolutionary Computation (CEC), 2013 IEEE Congress on. IEEE, pp. 939-946. 10.1109/CEC.2013.6557668

[thumbnail of CEC2013.pdf]
Preview
PDF - Published Version
Download (327kB) | Preview

Abstract

The urban transit routing problem (UTRP) involves finding efficient routes in a public transport system. However, developing effective heuristics and metaheuristics for the UTRP is hugely challenging because of the vast search space and multiple constraints that make even the attainment of feasible results exceedingly difficult, as the problem size increases. Moreover, progress with academic research on the UTRP appears to be seriously hampered by: 1) a lack of benchmark data, and 2) the complex and diverse range of methods used in the literature to evaluate solution quality. It is not currently possible for researchers to effectively compare the performance of their algorithms with anyone else's. This paper presents new problem-specific genetic operators within a multi-objective evolutionary framework, and furthermore proposes an effective and efficient heuristic method for seeding the population with feasible route sets. In addition new data sets are provided and made available for download, to aid future researchers. Excellent results are presented for Mandl's problem, which is currently the only benchmark available, while the results obtained for the new data sets provide a challenge for future researchers to beat.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
ISBN: 9781479904532
Date of First Compliant Deposit: 30 March 2016
Last Modified: 24 Oct 2022 11:50
URI: https://orca.cardiff.ac.uk/id/eprint/49465

Citation Data

Cited 61 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics