Departure timetable optimization based on NSGA-II

Yingxin Liu; Boning Wang

doi:10.1117/12.3039500

28 August 2024 Departure timetable optimization based on NSGA-II

Yingxin Liu, Boning Wang

Proceedings Volume 13251, Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024); 1325168 (2024) https://doi.org/10.1117/12.3039500
Event: 9th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024), 2024, Guilin, China

Abstract

This paper utilizes the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with an elite strategy for multi-objective optimization of bus timetables. In this study, three optimization objectives - passenger travel time, bus operation cost, and bus resource efficiency - are common and conflicting goals in optimizing bus route services. The algorithm’s findings indicate that the optimized timetable leads to a 10.2% reduction in passenger travel time, a 4% decrease in public transportation operating costs, and an 8.4% reduction in the index of public transport resource efficiency, thereby achieving partial optimization of the objectives. This notable improvement demonstrates the potential of multi-objective optimization methods in bus operation management.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yingxin Liu and Boning Wang "Departure timetable optimization based on NSGA-II", Proc. SPIE 13251, Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024), 1325168 (28 August 2024); https://doi.org/10.1117/12.3039500

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available