Multi-objective optimization for the green vehicle routing problem: A systematic literature review and future directions

Ferreira, Julio Cesar Batista; Steiner, María Teresinha Arns; Canciglieri, Osíris

doi:10.1080/23311916.2020.1807082

Cited by 13 publications

(6 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ferreira et al [18] reviewed 76 papers concerning the multi-objective version of GVRP, from 2012 to 2018. It primarily concentrated on the bibliometric analysis of ICV-based papers, including PRP, GVRP, and reverse logistics, while AFV-based papers were not considered.…”

Section: Previous Surveys On Gvrpmentioning

confidence: 99%

Metaheuristic approaches for the green vehicle routing problem

Matijević

2023

Yugosl J Oper Rres

View full text Add to dashboard Cite

The green vehicle routing problem (GVRP) is a relatively new topic, which aims to minimize greenhouse gasses (GHG) emissions produced by a fleet of vehicles. Both internal combustion vehicles (ICV) and alternative fuel vehicles (AFV) are considered, dividing GVRP into two separate subclasses: ICV-based GVRP and AFV-based GVRP. In the ICV-based subclass, the environmental aspect comes from the objective function which aims to minimize GHG emissions or fuel usage of ICVs. On the other hand, the environmental aspect of AFV-based GVRP is implicit and comes from using AFVs in transport. Since GVRP is NP-hard, finding the exact solution in a reasonable amount of time is often impossible for larger instances, which is why metaheuristic approaches are predominantly used. The purpose of this study is to detect gaps in the literature and present suggestions for future research in the field. For that purpose, we review recent papers in which GVRP was tackled by some metaheuristic methods and describe algorithm specifics, VRP attributes, and objectives used in them.

show abstract

Section: Previous Surveys On Gvrpmentioning

confidence: 99%

Metaheuristic approaches for the green vehicle routing problem

Matijević

2023

Yugosl J Oper Rres

View full text Add to dashboard Cite

show abstract

“…Routing optimization in the context of EnFVs involves the determination of efficient and optimal routes for message transmission, considering various objectives and constraints [17,18]. The objectives in multi-objective message routing optimization typically include minimizing message delivery time, maximizing network throughput, reducing energy consumption, and ensuring reliable communication.…”

Section: Objectives and Constraints In Routing Optimizationmentioning

confidence: 99%

“…There is a critical need to develop routing algorithms that can effectively optimize message routing in these dynamic transportation systems and address the limitations of traditional routing algorithms [18]. Multi-objective optimization is highly important in the context of EnFVs due to several key reasons [10,14,23]:…”

Section: Importance Of Multi-objective Optimization In Enfvsmentioning

confidence: 99%

“…It is essential to acknowledge that individual studies may incorporate additional metrics based on the specific requirements and complexities of their EnFV routing scenarios. Based on the provided Table 4, it is evident that the GA-based studies cover a wide range of application domains, including FANETs [6], UAV path planning [54], UAV networks [55], VRPs [56], logistics distribution [58], emergency logistics [59], drone delivery systems [18], and medical supply delivery [71]. This indicates the diverse areas in which GA-based optimization techniques are being applied to enhance efficiency and effectiveness.…”

Section: Review Of Case Studies: Flying Vehicle Routing Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Objective Routing Optimization in Electric and Flying Vehicles: A Genetic Algorithm Perspective

Alolaiwy,

Hawsawi,

Zohdy

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

The advent of electric and flying vehicles (EnFVs) has brought significant advancements to the transportation industry, offering improved sustainability, reduced congestion, and enhanced mobility. However, the efficient routing of messages in EnFVs presents unique challenges that demand specialized algorithms to address their specific constraints and objectives. This study analyzes several case studies that investigate the effectiveness of genetic algorithms (GAs) in optimizing routing for EnFVs. The major contributions of this research lie in demonstrating the capability of GAs to handle complex optimization problems with multiple objectives, enabling the simultaneous consideration of factors like energy efficiency, travel time, and vehicle utilization. Moreover, GAs offer a flexible and adaptive approach to finding near-optimal solutions in dynamic transportation systems, making them suitable for real-world EnFV networks. While GAs show promise, there are also limitations, such as computational complexity, difficulty in capturing real-world constraints, and potential sub-optimal solutions. Addressing these challenges, the study highlights several future research directions, including the integration of real-time data and dynamic routing updates, hybrid approaches with other optimization techniques, consideration of uncertainty and risk management, scalability for large-scale routing problems, and enhancing energy efficiency and sustainability in routing. By exploring these avenues, researchers can further improve the efficiency and effectiveness of routing algorithms for EnFVs, paving the way for their seamless integration into modern transportation systems.

show abstract

“…It is worth mentioning that recent and comprehensive review on GVRSP from various perspectives can be found in Moghdani et al [38] and Ferreira et al [39].…”

Section: Optimization and Scheduling Groupmentioning

confidence: 99%

The Adoption of Green Vehicles in Last Mile Logistics: A Systematic Review

et al. 2020

View full text Add to dashboard Cite

Widespread adoption of green vehicles in urban logistics may contribute to the alleviation of problems such as environmental pollution, global warming, and oil dependency. However, the current adoption of green vehicles in the last mile logistics is relatively low despite many actions taken by public authorities to overcome the negative externalities of distributing goods in cities. This paper presents a comprehensive literature review on studies investigating the adoption of green vehicles in urban freight transportation, paying specific attention to e-commerce. To shed light on the adoption of green vehicles in city logistics, the paper conducts a systematic review of the empirical literature on the topic. The 159 articles reviewed were classified into the following: (a) Optimization and scheduling (67 papers); (b) policy (55 papers); (c) sustainability (37 papers). Among the 159 articles, a further selection of 17 papers dealing with e-commerce, i.e., studies that highlight the most relevant aspects related to the integration of green vehicles in e-commerce urban logistics, was performed. Our findings indicate that green vehicles are competitive in urban deliveries characterized by frequent stop-and-go movements and low consolidation levels while incentives are still necessary for their adoption. The use of autonomous vehicles results the most promising and challenging solution for last-mile logistics.

show abstract

Multi-objective optimization for the green vehicle routing problem: A systematic literature review and future directions

Cited by 13 publications

References 74 publications

Metaheuristic approaches for the green vehicle routing problem

Metaheuristic approaches for the green vehicle routing problem

Multi-Objective Routing Optimization in Electric and Flying Vehicles: A Genetic Algorithm Perspective

The Adoption of Green Vehicles in Last Mile Logistics: A Systematic Review

Contact Info

Product

Resources

About