The Green-Vehicle Routing Problem: A Survey

Macrina, Giusy; Pugliese, Luigi Di Puglia; Guerriero, Francesca

doi:10.1007/978-3-030-45308-4_1

Cited by 14 publications

(7 citation statements)

References 85 publications

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“…Tinjauan mengenai tantangan lingkungan, strategi, dan operasional integrasi kendaraan listrik dalam aktivitas logistik dan transportasi dilakukan oleh Juan et al [7]. Survei tentang hasil-hasil penelitian yang berkaitan dengan green vehicle routing problem (GVRP) diberikan oleh Macrina et al [8]. EVRP menjadi semakin penting karena pertumbuhan eksponensial kendaraan listrik di sektor transportasi akhir-akhir ini secara global [9] maupun di Indonesia [10].…”

Section: Pendahuluanunclassified

Optimalitas Rute pada Pengiriman Multiperjalanan dengan Armada Kendaraan Listrik Heterogen

Salsabilla,

Bakhtiar,

Hanum

2024

Jambura J. Math

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Electric vehicles are emerging as a key trend in sustainable mobility, mitigating emissions, and reducing dependence on fossil fuels. The challenge in optimizing route modeling lies in some limitations, such as battery range, charging time, and the diversity of electric vehicle types. This article explores the optimality of routes in a multiple-trip distribution system using a heterogeneous fleet of electric vehicles. The electric vehicle routing problem is formulated as a mixed-integer linear programming aiming to find the most cost-efficient optimal route. A notable feature of the model allows electric vehicle fleets to undertake additional travel to complete distribution tasks, i.e., multiple trips. The model is implemented in two illustrative examples involving the delivery of goods using homogeneous and heterogeneous electric vehicle fleets characterized by loading and battery capacities. Each case includes one depot, 8 and 10 customers, and 2 battery swapping stations, solved using the branch-and-bound method through Lingo 18.0. Simulation results indicate that battery capacity and the presence of battery swapping stations significantly influence the routes selection.

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Section: Pendahuluanunclassified

Optimalitas Rute pada Pengiriman Multiperjalanan dengan Armada Kendaraan Listrik Heterogen

Salsabilla,

Bakhtiar,

Hanum

2024

Jambura J. Math

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“…Macrina et al [9] focused on building an up-to-date classification and discussing solution approaches for GVRP variants. +e authors identified two main classifications for GVRPs (e.g., GVRP with conventional vehicles and GVRP with alternative fuel vehicles).…”

Section: Related Workmentioning

confidence: 99%

“…As a result, the study of these methods has presented a considerable increase in the number of research works carried out especially in the last five years (see Figure 1). +e increased number of the applications around GVRPs is highlighted in various surveys, see for example, the reviews by Asghari and Mirzapour Al-e-hashem [6], Moghdani et al [7], Erdelić and Carić [8], and the book chapter by Macrina et al [9]. +ese reviews are focused on the problem domain and generally describe the solution approaches, but none of them analyzes nor details the basic features and components of the algorithms used to solve the GVRPs.…”

Section: Introductionmentioning

confidence: 99%

A Review of Heuristics and Hybrid Methods for Green Vehicle Routing Problems considering Emissions

Gil

Lalla-Ruiz

Sánchez

et al. 2022

Journal of Advanced Transportation

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Road freight transport is one of the sectors with the highest greenhouse gas emissions and fuel consumption in the logistics industry. In recent years, due to the increase in carbon dioxide emissions, several companies have considered reducing them in their daily logistics operations by means of better routing management. Green vehicle routing problems (GVRPs) constitute a growing problem direction within the interplay of vehicle routing problems and environmental sustainability that aims to provide effective routes while considering environmental concerns. These NP-hard problems are one of the most studied ones in green logistics, and due to their difficulty, there are many different heuristic and hybrid techniques to solve them under the need of having high-quality solutions within reasonable computational time. Given the role and importance of these methods, this review aims at providing a comprehensive overview of them while reviewing their defining strategies and components. In addition, we analyze characteristics and problem components related to how emissions are being considered. Lastly, we map and analyze the benchmarks proposed so far for the different GVRP variants considering emissions.

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“…The literature available in the domain has been reviewed in the following paragraphs. The studies shown against References 14 and 15 provide a more detailed information.…”

Section: Introductionmentioning

confidence: 99%

A mat‐heuristics approach for electric vehicle route optimization under multiple recharging options and time‐of‐use energy prices

Aggarwal

Rani

Bedi

et al. 2023

Concurrency and Computation

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SummaryTraveling has contributed a lot to the evolution of mankind. Today, electric vehicles (EVs) are being preferred due to their greater efficiency, comfort, and environment‐friendly qualities. The EVs' contribution to future mobility is projected to rise exponentially in years to come. To make this innovative technology more successful, there is a dire need to install a sufficient number of charging stations (CSs). As the EVs are limited by their cruising range, they require multiple recharging to cover long distances (especially in the case of logistics delivery services). Thus, there is a great need to develop an efficient and cost‐effective EV route optimization approach considering multiple recharging options and time‐of‐use (ToU) energy prices. In this regard, a novel mat‐heuristic approach named (firefly with ant colony algorithm) has been proposed to solve the problem of EVRPTW (electric vehicle routing problem with time windows) incorporating detailed modeling of multiple charging flexibility (i.e., battery swapping, partial recharge, and different charging levels) and ToU energy prices. Our proposed approach aims to minimize the total cost of traveling, which is highly influenced by the cost of recharging. Ant colony algorithm (ACA) serves as the basic optimization framework in the proposed approach, while the firefly approach explores hitherto unexplored solution space and avoids local optima. The computation performance of the proposed approach is compared with existing state‐of‐the‐art similar domain approaches such as variable neighborhood search (VNS) and ant colony optimization using local search (ACO‐LS) which has average deviation of nearly 20%–25% from with optimal solution achieved by the proposed . The proposed approach yields a near‐optimal solution with a faster convergence rate (approximately 50%) compared to other existing approaches. Moreover, the multiple recharging options modeled in our proposed approach justify their significance in terms of cost‐effectiveness for most scenarios.

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The Green-Vehicle Routing Problem: A Survey

Cited by 14 publications

References 85 publications

Optimalitas Rute pada Pengiriman Multiperjalanan dengan Armada Kendaraan Listrik Heterogen

Optimalitas Rute pada Pengiriman Multiperjalanan dengan Armada Kendaraan Listrik Heterogen

A Review of Heuristics and Hybrid Methods for Green Vehicle Routing Problems considering Emissions

A mat‐heuristics approach for electric vehicle route optimization under multiple recharging options and time‐of‐use energy prices

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