A Linear MIP Model for the Electric Vehicle Routing Problem with Time Windows Considering Linear Charging

Zuo, Xiaorong; Xiao, Yiyong; Zhu, Chuan; Meng, You

doi:10.1109/ram.2018.8463021

Cited by 11 publications

(4 citation statements)

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“…In [26], the path is planned based on a horizontal backoff strategy, which considers dynamic environments. Considering the practical problem in more detail, the vehicle PF problem with time windows is solved using mixed-integer programming (MIP) in [27]. Few articles take into account the human factor for MAPD problem, so we focus on the Problem (HS) 2 PD.…”

Section: A Related Workmentioning

confidence: 99%

Towards Safe and Efficient Swarm-Human Collaboration: A Hierarchical Multi-Agent Pickup and Delivery framework

Gong¹,

Wang²,

Cui³

et al. 2022

Preprint

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The multi-Agent Pickup and Delivery (MAPD) problem is crucial in the realm of Intelligent Storage Systems (ISSs), where multiple robots are assigned with time-varying, heterogeneous, and potentially uncertain tasks. When it comes to Human-Swarm Hybrid System ((HS) 2 ), robots and human workers will accomplish the MAPD tasks in collaboration. Herein, we propose a Human-Swarm Hybrid System Pickup and Delivery ((HS) 2 PD) framework, which is predominant in future ISSs. A two-layer decision framework based on the prediction horizon window is established in light of the unpredictability of human behavior and the dynamic changes of tasks. The first layer is a two-level programming problem to solve the problems of mode assignment and TA. The second layer is devoted to the exact path of each agent via solving mixed-integer programming (MIP) problems. An integrated algorithm for the (HS) 2 PD problem is summarized. The practicality and validity of the above algorithm are illustrated via a numerical simulation example towards (HS) 2 PD tasks.

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Section: A Related Workmentioning

confidence: 99%

Towards Safe and Efficient Swarm-Human Collaboration: A Hierarchical Multi-Agent Pickup and Delivery framework

Gong¹,

Wang²,

Cui³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…There are some works that combine the vehicle routing problem with the EV charging problem. Zuo et al [27] studied the VRP of EVs with time-window with logistics maintenance optimization. Chen et al [5] combined EV charging with pickup delivery problems for joint routing and charging of EVs with taking electricity price and customer satisfaction into account.…”

Section: Related Workmentioning

confidence: 99%

Online Routing and Charging Schedule of Electric Vehicles With Uninterrupted Charging Rates

Cao

2022

IEEE Access

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With the development of electric vehicle technology and the Internet of Things (IoT) technology, IoT-Based electric vehicles (IoEVs) will become a main public transposition in smart city. The increasing penetration of IoEV will have a great impact on the transportation network and power grid. In this work, we aim to study the routing and charging scheduling problem of IoEVs with the constraint of power limit. This paper proposes a clustered rolling framework and a mathematical model for the IoEVs optimal routing and charging problem to minimize the waiting time of customers and get a good converge ratio of the energy block with power limit. This framework can effectively deal with the multi-step pickup and delivery of each vehicle over the time horizon in a dynamic environment. We give a criterion to judge whether pickup and delivery tasks can be assigned to the IoEV. Then, we design a new rectangle packing method for IoEV charging dispatch with the constraint of power limit. Moreover, we consider that the charging process of IoEVs cannot be interrupted before IoEVs meet the electricity demand. We propose the IoEV Routing and Charging Algorithm and analyze its computational complexity. Simulation results show that IoEVs can offer the shuttle service to customers with the minimum waiting time and IoEV charging energy block has a good coverage ratio of the total energy block. Simulation results can verify the effectiveness of our proposed framework, compared with two benchmark algorithms.INDEX TERMS IoT-Based electric vehicle, clustered rolling framework, pickup and delivery, routing and charging, rectangle packing algorithm.

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“…Kancharla and Ramadurai [66] considered significant parameters such as speed, acceleration, load, and grade, which affect the battery consumption rate, and estimated the amount of energy required by the EV engine. Zuo et al [67] applied factors such as limited battery capacity, charging station selection, and determining the battery charging time to improve the efficiency of EVs in the logistics system. Keskin et al [40] developed the problem considering time-dependent queueing times at the stations.…”

Section: Electric Vehicle Routing Problem With Time Windows (E-vrp-tw)mentioning

confidence: 99%

A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification

et al. 2020

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The growth of environmental awareness and more robust enforcement of numerous regulations to reduce greenhouse gas (GHG) emissions have directed efforts towards addressing current environmental challenges. Considering the Vehicle Routing Problem (VRP), one of the effective strategies to control greenhouse gas emissions is to convert the fossil fuel-powered fleet into Environmentally Friendly Vehicles (EFVs). Given the multitude of constraints and assumptions defined for different types of VRPs, as well as assumptions and operational constraints specific to each type of EFV, many variants of environmentally friendly VRPs (EF-VRP) have been introduced. In this paper, studies conducted on the subject of EF-VRP are reviewed, considering all the road transport EFV types and problem variants, and classifying and discussing with a single holistic vision. The aim of this paper is twofold. First, it determines a classification of EF-VRP studies based on different types of EFVs, i.e., Alternative-Fuel Vehicles (AFVs), Electric Vehicles (EVs) and Hybrid Vehicles (HVs). Second, it presents a comprehensive survey by considering each variant of the classification, technical constraints and solution methods arising in the literature. The results of this paper show that studies on EF-VRP are relatively novel and there is still room for large improvements in several areas. So, to determine future insights, for each classification of EF-VRP studies, the paper provides the literature gaps and future research needs.

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A Linear MIP Model for the Electric Vehicle Routing Problem with Time Windows Considering Linear Charging

Cited by 11 publications

References 11 publications

Towards Safe and Efficient Swarm-Human Collaboration: A Hierarchical Multi-Agent Pickup and Delivery framework

Towards Safe and Efficient Swarm-Human Collaboration: A Hierarchical Multi-Agent Pickup and Delivery framework

Online Routing and Charging Schedule of Electric Vehicles With Uninterrupted Charging Rates

A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification

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