Routing Electric Vehicles on Congested Street Networks

Florio, Alexandre M.; Absi, Nabil; Feillet, Dominique

doi:10.1287/trsc.2020.1004

Cited by 29 publications

(13 citation statements)

References 45 publications

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“…This is clearly too demanding to apply to every label generated by the pricing algorithm. For this reason, we employ the speed-up procedure proposed in Florio et al (2021a). Before starting the labeling algorithm, we select a subset of customers M ⊂ {1, .…”

Section: Rcsp-based Boundsmentioning

confidence: 99%

Vehicle Routing with Stochastic Demands and Partial Reoptimization

Florio,

Feillet,

Poggi

et al. 2022

Preprint

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We consider the vehicle routing problem with stochastic demands (VRPSD), a problem in which customer demands are known in distribution at the route planning stage and revealed during route execution upon arrival at each customer. A long-standing open question on the VRPSD concerns the benefits of allowing, during route execution, partial reordering of the planned customer visits. Given the practical importance of this question and the growing interest on the VRPSD under optimal restocking, we study the VRPSD under a recourse policy known as the switch policy. The switch policy is a canonical reoptimization policy that permits only pairs of successive customers to be reordered. We consider this policy jointly with optimal preventive restocking and introduce a branch-cut-and-price algorithm to compute optimal a priori routing plans in this context. At its core, this algorithm features pricing routines where value functions represent the expected cost-to-go along planned routes for all possible states and reordering decisions. To ensure pricing tractability, we adopt a strategy that combines elementary pricing with completion bounds of varying complexity, and solve the pricing problem without relying on dominance rules. Our numerical experiments demonstrate the effectiveness of the algorithm for solving instances with up to 50 customers. Notably, they also give us new insights into the value of reoptimization. The switch policy enables significant cost savings over optimal restocking when the planned routes come from an algorithm built on a deterministic approximation of the data, an important scenario given the difficulty of finding optimal VRPSD solutions. The benefits are smaller when comparing optimal a priori VRPSD solutions obtained for both recourse policies.As it appears, further cost savings may require joint reordering and reassignment of customer visits among vehicles when the context permits.

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Section: Rcsp-based Boundsmentioning

confidence: 99%

Vehicle Routing with Stochastic Demands and Partial Reoptimization

Florio,

Feillet,

Poggi

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…According to Florio et al [135], EVs route planning must always consider their relatively short autonomy and the effects of traffic congestion on battery consumption. Therefore, they propose a new methodology that serves as a framework for optimization algorithms to solve the E-VRP with stochastic and time-dependent travel times without allowing battery recharging along the way.…”

Section: E-vrps Focusing On Battery Rechargementioning

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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“…Proper logistical planning is also essential in connection with the knowledge of the specifics of electric vehicle operation, especially in urban applications. Florio et al provide a relevant methodology in their study for solving the electric vehicle problem on congested street networks [18]. Electric vehicle turnover planning is also addressed in a study by Rubiano et al, who use simulation mathematical-heuristic methods [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Research into the Impacts of Driving Cycles and Load Weight on the Operation of a Light Commercial Electric Vehicle

et al. 2021

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The European Parliament has adopted Directive 2019/1161 on the promotion of environmentally friendly and energy-efficient road transport vehicles, which also defines the obligations and forms of support for the procurement of environmentally friendly vehicles in urban logistics. The increase in the number of shipments delivered within e-commerce, which is also the result of the COVID-19 pandemic, requires a transition to a sustainable logistics system. New research questions are being raised in the preparation of new projects for the introduction of small electric commercial vehicles in particular. One of the main research questions about deployment itself is whether light commercial electric vehicles are able to fully replace conventionally powered vehicles. What operating conditions are optimal for the operation of them? How does load weight affect the energy efficiency of operating a light commercial electric vehicle? The authors decided to carry out research into the impacts of weight and the nature of a driving cycle under laboratory conditions to eliminate all external factors that could distort individual measurements and their results. In order to simulate driving cycles, an urban driving cycle was designed on the basis of the course of speed, acceleration, deceleration and slope conditions of roads in the selected regional city of Žilina (Slovakia). In the case of the operation of an electrically powered light commercial vehicle, the impact of load weight on the range of the vehicle is low, and is below the level of the theoretical maximum range of the vehicle in urban logistics applications. The operation of electrically powered vehicles in hilly terrains with relatively longer gradients and steeper slopes increases electricity consumption and, thereby, reduces their range.

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Routing Electric Vehicles on Congested Street Networks

Cited by 29 publications

References 45 publications

Vehicle Routing with Stochastic Demands and Partial Reoptimization

Vehicle Routing with Stochastic Demands and Partial Reoptimization

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

Research into the Impacts of Driving Cycles and Load Weight on the Operation of a Light Commercial Electric Vehicle

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