Clustered tabu search optimization for reservation-based shared autonomous vehicles
This paper investigates the optimization of Reservation-based Autonomous Car Sharing (RACS) systems, aiming at minimizing the total vehicle travel time and customer waiting time. Thus, the RACS system and its routing are formulated with a consideration for system efficiency and passengers’ concerns. A meta-heuristic Tabu search method is investigated as a solution approach, in combination with K–Means (KMN–Tabu) or K–Medoids (KMD–Tabu) clustering algorithms. The proposed solution algorithms are tested in two different networks of varying complexity, and the performance of the algorithms is evaluated. The evaluation results show that the TS method is more suitable for small-scale problems, while KMD–Tabu is suitable for large-scale problems. However, KMN-Tabu has the least computation time, although the solution quality is lower.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/19427867
-
Supplemental Notes:
- © 2020 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
-
Authors:
- Su, Shun
- Chaniotakis, Emmanouil
- Narayanan, Santhanakrishnan
- Jiang, Hai
- Antoniou, Constantinos
- Publication Date: 2022-2
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 124-128
-
Serial:
- Transportation Letters: The International Journal of Transportation Research
- Volume: 14
- Issue Number: 2
- Publisher: Taylor & Francis
- ISSN: 1942-7867
- EISSN: 1942-7875
- Serial URL: http://www.tandfonline.com/toc/ytrl20/current
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Optimization; Reservations; Routing; Tabu search; Vehicle sharing
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation; Vehicles and Equipment;
Filing Info
- Accession Number: 01839937
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 24 2022 5:26PM