A robust multi-objective routing problem for heavy-duty electric trucks with uncertain energy consumption

Amiri, Afsane; Zolfagharinia, Hossein; Amin, Saman Hassanzadeh

doi:10.1016/j.cie.2023.109108

Cited by 11 publications

(2 citation statements)

References 44 publications

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“…Each vehicle has its own load capacity. Our aim is to ensure that the demands D w (∀ w ∈ C t ) carried by a given vehicle y (∀ y ∈ V h ) do not surpass its capacity Cap y y (∀ y ∈ V h ), and that is guaranteed by constraint (30).…”

Section: Capacity Constraintsmentioning

confidence: 99%

Electric Vehicle Routing Problem with an Enhanced Vehicle Dispatching Approach Considering Real-Life Data

Abid,

Tabaa,

Hachimi

2024

Energies

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Although the EVRP (Electric Vehicle routing problem) has promising results on the environmental scale, its implementation has proved challenging. The difficulty of the EVRP resides in the limited driving range of the electric vehicles, combined with the significant charging time. While the charging cost is less than the cost of fuel, this charge time adds to the overall travel time and may overlap with customers’ time windows. All these factors increased the computational time exponentially and resulted in the need to overlook some constraints such as traffic congestion, road conditions, weather impact on energy consumption, and driving style, to name a few, in order to speed up execution time. While this method proved effective in accelerating the process of the EVRP, it did, however, render the approach unrealistic, as it steered far from real-life settings and made the approach unpredictable when facing dynamic and changing parameters. In this paper, we try to remedy this issue by proposing an approach in which we try to replicate real-life parameters such as heterogenous fleets, energy consumption, and infrastructure data. The objective of our approach was to minimize the total travel time, travel distance, energy consumed, and the number of vehicles deployed. To solve this problem, we propose a three-stages approach, in which the first stage consists of a newly developed dispatching approach where customers are assigned to vehicles. The second stage uses the genetic algorithm to find a set of optimal paths, and, finally, in the third stage, charging stations are inserted in the selected paths. Upon testing our approach on Solomon’s instances, our approach proved effective in finding optimal solutions in a reasonable time for five- to fifteen-customer datasets. However, when trying to solve larger datasets, the approach was slowed down by the extreme number of constraints it had to satisfy.

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Section: Capacity Constraintsmentioning

confidence: 99%

Electric Vehicle Routing Problem with an Enhanced Vehicle Dispatching Approach Considering Real-Life Data

Abid,

Tabaa,

Hachimi

2024

Energies

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“…This latter area has recently become the subject of greater attention. The promotion of electric vehicles (EVs) poses a huge challenge for the transport sector, especially in the process of optimizing travel routes [21][22][23], but also for the energy sector [24][25][26][27]. Unfortunately, it has often been forgotten that the proper development of electromobility must go alongside the simultaneous development of the energy sector [24].…”

Section: Introductionmentioning

confidence: 99%

The Novel Approach of Using Electric Vehicles as a Resource to Mitigate the Negative Effects of Power Rationing on Non-Residential Buildings

Zagrajek,

Kłos,

Rasolomampionona

et al. 2023

Energies

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This paper presents the concept of using electric vehicles (EVs) as a countermeasure to deal with the negative effects of power rationing when electricity demands become difficult to meet due to unfavorable electrical system operating conditions. At present, an energy storage is widely used to maintain the stability of electricity supply in facilities whose main source of energy is renewable energy sources (RESs). However, we must not forget that electric vehicles are also electricity storage facilities, but they are not always available due to their mobility. With properly developed strategies, they can be used in electricity management processes, for example, by reducing their consumption during charging using smart charging technology, or by providing electricity from their batteries using vehicle-to-building (V2B) technology. Thus, this article presents a research methodology that treats electric vehicles as a remedy for eliminating power constraints. It consists of five main steps, including two algorithms for deciding how to deploy EVs during power rationing periods. An efficiency factor for eliminating these constraints was also introduced. The results showed that the use of smart charging or V2B technology in EVs can reduce the number of potential hours in which certain power levels are exceeded by up to several tens of percent. This means that in the future, with the significant development of electromobility, such a way of dealing with power constraints could be an alternative to conventional solutions like diesel generators.

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The vehicle routing programming of municipal solid waste collection under cognitive uncertainty

Wang,

Huo,

Lam

2024

Transp. j.

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The rapid development of online shopping has led to an increase in express parcels, thus the proliferation of solid waste from parcel packaging. There are many other phenomena that have arisen with rapid economic development that also led to the surge in municipal solid waste. It is urgent to pay attention to municipal solid waste collection. Unexpected disruptive events lead to cognitive uncertainty and cause municipal waste collection to fail to function properly. This article studies how to properly carry out vehicle planning to achieve the shortest driving distance under cognitive uncertainty. The community's time window and the amount of garbage in each community are taken as uncertain variables. Based on the uncertainty theory, an uncertain vehicle routing problem (VRP) model and an uncertain VRP with the loading constraint model are constructed, and the solution algorithms of these two models are given. Several applications are carried out to evaluate the effectiveness of the proposed models and algorithms. This article proposes for the first time the models and algorithms to study the VRP under cognitive uncertainty. The findings draw important practical implications for adjusting municipal solid waste collection planning and logistics during disruptive events.

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A robust multi-objective routing problem for heavy-duty electric trucks with uncertain energy consumption

Cited by 11 publications

References 44 publications

Electric Vehicle Routing Problem with an Enhanced Vehicle Dispatching Approach Considering Real-Life Data

Electric Vehicle Routing Problem with an Enhanced Vehicle Dispatching Approach Considering Real-Life Data

The Novel Approach of Using Electric Vehicles as a Resource to Mitigate the Negative Effects of Power Rationing on Non-Residential Buildings

The vehicle routing programming of municipal solid waste collection under cognitive uncertainty

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