Access the full text.
Sign up today, get DeepDyve free for 14 days.
J Desrosiers, JB Gauthier, ME Lübbecke (2014)
Row-reduced column generation for degenerate master problemsEur J Oper Res, 236
D Huisman, R Jans, M Peters, APM Wagelmans (2005)
Column generation
JK Lenstra, AHG Rinnooy Kan (1981)
Complexity of vehicle routing and scheduling problemsNetworks, 11
M Schneider, A Stenger, D Goeke (2014)
The electric vehicle routing problem with time windows and recharging stationsTransp Sci, 48
M Huang, J-Q Li (2016)
The shortest path problems in battery-electric vehicle dispatching with battery renewalSustainability, 8
A-S Pepin, G Desaulniers, A Hertz, D Huisman (2009)
A comparison of five heuristics for the multiple depot vehicle scheduling problemJ Sched, 12
M Bruglieri, F Pezzella, O Pisacane, S Suraci (2015)
A variable neighborhood search branching for the electric vehicle routing problem with time windowsElectron Notes Discrete Math, 47
MR Garey, DS Johnson (1979)
Computers and intractability: a guide to the theory of NP-completeness
J-Q Li (2014)
Transit bus scheduling with limited energyTransp Sci, 48
O Sassi, A Oulamara (2017)
Electric vehicle scheduling and optimal charging problem: complexity, exact and heuristic approachesInt J Prod Res, 55
The vehicle scheduling problem (VSP) is a traditional problem in public transport. One of the main assumptions is that buses can be operated the whole day without any interruption for refueling etc. Recently, new technological innovations have led to the introduction of electric vehicles (EVs). For these new vehicles, we cannot ignore the need of refueling during the day, as the range of an electric bus is severely limited, because of the capacity of the batteries. In this paper, we study the electric VSP (e-VSP), where we use EVs with a limited range. During the day the batteries can be charged; in this paper we assume that a battery cannot be replaced/substituted. We present two models that differ in the level of detail resembling the actual processes. In our first model, we assume a linear charging process, work with a constant price of electricity during the day, and do not take the effect of the depth-of-discharge on the lifetime of the battery into account. Our second model resembles practice much better: we allow any type of charging process, work with the actual electricity prices, and take the depreciation cost of the battery into account. To keep this model tractable, however, we approximate the exact value of the charge by discretizing it. The refined model can be solved to optimality using integer linear programming for instances of small/medium size, and therefore, we describe two other solution methods based on column generation that find good, but not necessarily optimal, solutions for large instances. We have tested our algorithms on real-world instances.
Public Transport – Springer Journals
Published: Jun 12, 2017
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.