Electric Vehicle Routing Problem With Variable Vehicle Speed and Soft Time Windows for Perishable Product Delivery

Liu, Zhishuo; Zuo, Xingquan; Zhou, MengChu; Guan, Wei; Al‐Turki, Yusuf

doi:10.1109/tits.2023.3249403

Cited by 14 publications

(1 citation statement)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…IDJaya has the potential to be extended to solve other path problems, such as the constrained SPP and path planning problems in dynamic and 3-D networks. Its combination with recent deep learning methods [69][70][71][72][73] should be investigated to handle large-scale processes and systems [74][75][76][77][78][79][80][81][82][83][84]. Additionally, we are interested in considering the application of IDJaya to practical scenarios, i.e., industrial robots [39][40][41], automatic guided vehicle (AGV) [85,86], autonomous driving [87], resource scheduling [88,89] and multi-agent systems [77,[90][91][92][93].…”

Section: Discussionmentioning

confidence: 99%

An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes

et al. 2023

Self Cite

View full text Add to dashboard Cite

Shortest path problems are encountered in many engineering applications, e.g., intelligent transportation, robot path planning, and smart logistics. The environmental changes as sensed and transmitted via the Internet of Things make the shortest path change frequently, thus posing ever-increasing difficulty for traditional methods to meet the real-time requirements of many applications. Therefore, developing more efficient solutions has become particularly important. This paper presents an improved discrete Jaya algorithm (IDJaya) to solve the shortest path problem. A local search operation is applied to expand the scope of solution exploration and improve solution quality. The time complexity of IDJaya is analyzed. Experiments are carried out on seven real road networks and dense graphs in transportation-related processes. IDJaya is compared with the Dijkstra and ant colony optimization (ACO) algorithms. The results verify the superiority of the IDJaya over its peers. It can thus be well utilized to meet real-time application requirements.

show abstract

Section: Discussionmentioning

confidence: 99%

An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

Evolving routing policies for electric vehicles by means of genetic programming

Gil-Gala,

Đurasević,

Jakobović

2024

Appl Intell

View full text Add to dashboard Cite

In recent years, the growing interest in environmental sustainability has led to Electric Vehicle Routing Problems (EVRPs) attracting more and more attention. EVRPs involve the use of electric vehicles, which have additional constraints, such as range and recharging time, compared to conventional Vehicle Routing Problems (VRPs). The complexity and dynamic nature of solving VRPs often lead to the introduction of Routing Policies (RPs), simple heuristics that incrementally build routes. However, manually designing efficient RPs proves to be a challenging and time-consuming task. Therefore, there is a pressing need to explore the application of hyper-heuristics, in particular Genetic Programming (GP), to automatically generate new RPs. Since this method has not yet been investigated in the literature in the context of EVRPs, this study explores the applicability of GP to automatically generate new RPs for EVRP. To this end, three RP variants (serial, semiparallel, and parallel) are introduced in this study, along with a set of domain-specific terminal nodes to optimise three criteria: the number of vehicles, energy consumption, and total tardiness. The experimental analysis shows that the serial variant performs best in terms of energy consumption and number of vehicles, while the parallel variant is most effective in minimising the total tardiness. A comprehensive analysis of the proposed method is conducted to determine its convergence properties and the impact of the proposed terminal nodes on performance and to describe several generated RPs. The results show that the automatically generated RPs perform commendably compared to traditional methods such as metaheuristics and exact methods, which usually require significantly more runtime. More specifically, depending on the scenario in which they are used, the generated RPs achieve results that are about 20%-37% worse compared to the best known results for the number of vehicles in almost negligible time, in just some milliseconds.

show abstract

Optimizing electric vehicle routing with nonlinear charging and time windows using improved differential evolution algorithm

Deng,

Zhang,

Yang

2024

Cluster Comput

View full text Add to dashboard Cite

Electric Vehicle Routing Problem With Variable Vehicle Speed and Soft Time Windows for Perishable Product Delivery

Cited by 14 publications

References 30 publications

An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes

An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes

Evolving routing policies for electric vehicles by means of genetic programming

Optimizing electric vehicle routing with nonlinear charging and time windows using improved differential evolution algorithm

Contact Info

Product

Resources

About