Multiple tabu search for multiobjective urban transit scheduling problem

The study of urban public transportation is essential for building an efficient transit system that can minimize the traffic congestion, reduce pollutions and increase the mobility of a community. Urban Transit Scheduling Problem (UTSP) considers the process of creating timely transit schedules that...

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Hlavní autoři: Uvaraja, Vikneswary, Lai, Soon Lee, Ab. Rahmin, Nor Aliza
Médium: Článek
Vydáno: Academy of Sciences Malaysia 2019
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author Uvaraja, Vikneswary
Lai, Soon Lee
Ab. Rahmin, Nor Aliza
author_facet Uvaraja, Vikneswary
Lai, Soon Lee
Ab. Rahmin, Nor Aliza
author_sort Uvaraja, Vikneswary
collection UPM
description The study of urban public transportation is essential for building an efficient transit system that can minimize the traffic congestion, reduce pollutions and increase the mobility of a community. Urban Transit Scheduling Problem (UTSP) considers the process of creating timely transit schedules that includes bus and drivers assignment based on the users’ and operators’ requirements. It is necessary to achieve a tradeoff between the interest of users and operators which lead to multiobjective nature of UTSP. This paper studies multiobjective UTSP consisting of frequency setting, timetabling, simultaneous bus and driver scheduling by applying a Multiple Tabu Search (MTS) algorithm. In addition, a multiobjective set covering model is also adapted by including some real-world restrictions to find adequate number of buses and drivers. The MTS algorithm is tested on benchmark instances from Mandl’s Swiss Network. The computational results shown that the algorithm able to produce comparable results for most cases from the literature.
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spelling upm.eprints-814432024-05-14T07:04:23Z http://psasir.upm.edu.my/id/eprint/81443/ Multiple tabu search for multiobjective urban transit scheduling problem Uvaraja, Vikneswary Lai, Soon Lee Ab. Rahmin, Nor Aliza The study of urban public transportation is essential for building an efficient transit system that can minimize the traffic congestion, reduce pollutions and increase the mobility of a community. Urban Transit Scheduling Problem (UTSP) considers the process of creating timely transit schedules that includes bus and drivers assignment based on the users’ and operators’ requirements. It is necessary to achieve a tradeoff between the interest of users and operators which lead to multiobjective nature of UTSP. This paper studies multiobjective UTSP consisting of frequency setting, timetabling, simultaneous bus and driver scheduling by applying a Multiple Tabu Search (MTS) algorithm. In addition, a multiobjective set covering model is also adapted by including some real-world restrictions to find adequate number of buses and drivers. The MTS algorithm is tested on benchmark instances from Mandl’s Swiss Network. The computational results shown that the algorithm able to produce comparable results for most cases from the literature. Academy of Sciences Malaysia 2019 Article PeerReviewed Uvaraja, Vikneswary and Lai, Soon Lee and Ab. Rahmin, Nor Aliza (2019) Multiple tabu search for multiobjective urban transit scheduling problem. ASM Science Journal, 12 (spec.1). pp. 150-173. ISSN 1823-6782; ESSN: 2682-8901 https://www.akademisains.gov.my/asmsj/article/multiple-tabu-search-for-multiobjective-urban-transit-scheduling-problem/#
spellingShingle Uvaraja, Vikneswary
Lai, Soon Lee
Ab. Rahmin, Nor Aliza
Multiple tabu search for multiobjective urban transit scheduling problem
title Multiple tabu search for multiobjective urban transit scheduling problem
title_full Multiple tabu search for multiobjective urban transit scheduling problem
title_fullStr Multiple tabu search for multiobjective urban transit scheduling problem
title_full_unstemmed Multiple tabu search for multiobjective urban transit scheduling problem
title_short Multiple tabu search for multiobjective urban transit scheduling problem
title_sort multiple tabu search for multiobjective urban transit scheduling problem
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AT laisoonlee multipletabusearchformultiobjectiveurbantransitschedulingproblem
AT abrahminnoraliza multipletabusearchformultiobjectiveurbantransitschedulingproblem