Scipediacontent: Scipediacontent moved page Draft Content 444037338 to Govinda Raja Perumal et al 2020a

2021-01-21T14:00:59Z

Scipediacontent moved page Draft Content 444037338 to Govinda Raja Perumal et al 2020a

Scipediacontent: Created page with " == Abstract == extabstractThe use of electric buses is expected to rise due to its environmental benefits. However, electric vehicles are less exible than conventional dies..."

2021-01-21T14:00:56Z

Created page with " == Abstract == extabstractThe use of electric buses is expected to rise due to its environmental benefits. However, electric vehicles are less exible than conventional dies..."

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== Abstract ==

extabstractThe use of electric buses is expected to rise due to its environmental benefits. However, electric vehicles are less exible than conventional diesel buses due to their limited driving range and longer recharging times. Therefore, scheduling electric vehicles adds further operational dificulties. Additionally, various labor regulations challenge public transport companies to find a cost-effcient crew schedule. Vehicle and crew scheduling problems essentially define the cost of operations. In practice, these two problems are often solved sequentially. In this paper, we introduce the integrated electric vehicle and crew scheduling problem (E-VCSP). Given a set of timetabled trips and recharging stations, the E-VCSP is concerned with finding vehicle and crew schedules that cover the timetabled trips and satisfy operational constraints, such as limited driving range of electric vehicles and labor regulations for the crew while minimizing total operational cost. An adaptive large neighborhood search that utilizes branch-and-price heuristics is proposed to tackle the E-VCSP. The proposed method is tested on real-life instances from public transport companies in Denmark and Sweden that contain up to 1,109 timetabled trips. The heuristic approach provides evidence of improving efficiency of transport systems when the electric vehicle and crew scheduling aspects are considered simultaneously. By comparing to the traditional sequential approach, the heuristic finds improvements in the range of 1.17-4.37% on average. A sensitivity analysis of the electric bus technology is carried out to indicate its implications for the crew schedule and the total operational cost. The analysis shows that the operational cost decreases with increasing driving range (120 to 250 kilometers) of electric vehicles.

== Original document ==

The different versions of the original document can be found in:

* [https://orbit.dtu.dk/en/publications/7bc6f2b8-8218-4a3e-9c4e-4d7c61ca8825 https://orbit.dtu.dk/en/publications/7bc6f2b8-8218-4a3e-9c4e-4d7c61ca8825],
: [https://backend.orbit.dtu.dk/ws/files/206553493/EI_2020_02.pdf https://backend.orbit.dtu.dk/ws/files/206553493/EI_2020_02.pdf],
: [http://hdl.handle.net/1765/123963 http://hdl.handle.net/1765/123963]

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Govinda Raja Perumal et al 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 444037338 to Govinda Raja Perumal et al 2020a

Scipediacontent: Created page with " == Abstract == extabstractThe use of electric buses is expected to rise due to its environmental benefits. However, electric vehicles are less exible than conventional dies..."