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Scheduling the vehicles of bus rapid transit systems: a case study
Author(s) -
Sevim İsmail,
TekinerMoğulkoç Hatice,
Güler Mehmet Güray
Publication year - 2022
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12763
Subject(s) - trips architecture , heuristics , bus rapid transit , scheduling (production processes) , computer science , transport engineering , public transport , operations research , fleet management , heuristic , mathematical optimization , engineering , mathematics , artificial intelligence , operating system
Abstract Bus rapid transit (BRT) is a cost‐efficient, traffic‐free bus‐based transportation system competing with subways. There are 205 municipalities around the world that implemented their own BRT systems. Istanbul, having the sixth‐most congested traffic in the world, built its own BRT system (Metrobüs), which serves more than 830,000 people (6.45% of all public transportation usage) in a day with 6254 trips covered by its current fleet of 496 vehicles. In this study, we model the vehicle scheduling problem of Metrobüs as a multiple depot vehicle scheduling problem. The model aims to minimize the fleet size and total deadhead kilometers while covering all timetabled trips. We propose a new heuristic, trips merger (TM), to solve the model and show that there exists cost reduction opportunities in terms of both fleet size and deadhead kilometers. The proposed heuristic is a member of the state‐space reduction heuristics family, which first reduces the problem size, then solves the reduced problem. Computational study reveals that TM performed better than the existing state‐space reduction heuristics for the Metrobüs case.