A tour recommendation service for electric vehicles based on a hybrid orienteering model

Lee, Junghoon; Kim, Sang–Wook; Park, Gyung-Leen

doi:10.1145/2480362.2480671

Cited by 13 publications

(6 citation statements)

References 5 publications

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“…From the experiments, the authors conclude that 95% of the selected spots could be visited without generating waiting times for tourists. A tour recommendation scheme for EVs is also proposed by Lee et al [180]. Their goal is to minimize the time waste induced by long charging times.…”

Section: Orienteering Problems With a Single Vehiclementioning

confidence: 99%

Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

et al. 2021

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The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.

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Section: Orienteering Problems With a Single Vehiclementioning

confidence: 99%

Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

et al. 2021

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“…The route will have the minimal tour length while the waiting time is kept below the permissible bound. The waiting time arises due to battery shortage while the EV begins the tour with its battery fully charged [2]. Every optimization problem defines its own object function which evaluates how well a solution fits for the given goal.…”

Section: Heuristic-based Design 21 Object Functionmentioning

confidence: 99%

Search space reduction for electric vehicle-based tour schedules

Lee

Park

2015

Proceedings of the 30th Annual ACM Symposium on Applied Computing

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This paper develops speedup techniques for tour schedules based on electric vehicle (EV)-specific constraint processing. Rather than the tour length, the waiting time is more critical to EVs due to long charging time and immature charging infrastructure. First, grouping tour spots in the vicinity significantly cuts down the search space, which is very sensitive to the number of destinations to visit, as the subsequence within a group has little impact on the waiting time. Second, the per-spot precalculation of the minimum cost to the other destinations makes more branches be pruned. Finally, the combination of well-established techniques in the traveling salesman problem leads to a tighter constraint on intermediary node expansion. The reduced overhead provides an acceptable response time for EV drivers who want to make an energy-efficient tour plan having a tolerable waiting time bound.

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“…Moreover, insertion of additional places, essentially having chargers, can further reduce the waiting time. Tourists prefer to visit another spot rather than to waste their time, even if the total tour length may increase [9]. As such, many types of tour schedule variants can be developed for the specific tour goals.…”

Section: Related Workmentioning

confidence: 99%