Compensation and profit allocation for collaborative multicenter vehicle routing problems with time windows DOI
Yong Wang, Siyu Luo,

Jianxin Fan

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 233, P. 120988 - 120988

Published: July 18, 2023

Language: Английский

Collaborative multidepot electric vehicle routing problem with time windows and shared charging stations DOI
Yong Wang, Jingxin Zhou, Yaoyao Sun

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 219, P. 119654 - 119654

Published: Feb. 4, 2023

Language: Английский

Citations

45
Optimizing COVID-19 medical waste management using goal and robust possibilistic programming DOI
Hamed Karimi,

Niaz A. Wassan,

Behdad Ehsani

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 131, P. 107838 - 107838

Published: Jan. 6, 2024

Language: Английский

Citations

21
The two-echelon truck-unmanned ground vehicle routing problem with time-dependent travel times DOI

Yuanhan Wei,

Yong Wang, Xiangpei Hu

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2025, Volume and Issue: 194, P. 103954 - 103954

Published: Jan. 8, 2025

Language: Английский

Citations

3
The Future of Last-Mile Delivery: Lifecycle Environmental and Economic Impacts of Drone-Truck Parallel Systems DOI Creative Commons
Danwen Bao,

Yu Yan,

Yuhan Li

et al.

Drones, Journal Year: 2025, Volume and Issue: 9(1), P. 54 - 54

Published: Jan. 14, 2025

With rapid advancements in unmanned aerial vehicle (UAV) technology, its integration into logistics operations has emerged as a promising solution for improving efficiency and sustainability. Among the emerging solutions, collaborative delivery model involving drones trucks addresses last-mile challenges by leveraging complementary strengths of both modes transport. However, evaluating environmental economic impacts this transportation mode requires systematic framework to capture unique characteristics minimize costs. This paper investigates Parallel Drone Scheduling Traveling Salesman Problem (PDSTSP) evaluate sustainability drone-truck system. Specifically, mathematical system is developed optimize joint operations. Environmental are assessed using comprehensive Life Cycle Assessment (LCA), including emissions operational noise, while Cost Analysis (LCCA) quantifies performance across five cost dimensions. Sensitivity analysis explores factors such density, traffic congestion, wind conditions. Results show that, compared electric fleet, proposed achieves an approximate 20% reduction carbon emissions, delivering 20–30% relative fuel truck fleet. Drones’ short-distance deliveries alleviates trucks’ load, cutting study offers practical insights recommendations implementing parallel systems, particularly high-demand density areas.

Language: Английский

Citations

3
Time-Dependent Vehicle Routing Problem with Drones Under Vehicle Restricted Zones and No-Fly Zones DOI Creative Commons

Shuo Wei,

Houming Fan,

Xiaoxue Ren

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 2207 - 2207

Published: Feb. 19, 2025

This paper addresses the time-dependent vehicle routing problem with drones in vehicle-restricted zones and no-fly (TDVRPD-VRZ-NFZ). The optimization model considers impacts of zones, road networks on delivery paths. objective is to minimize total cost, including dispatch costs, energy consumption costs for vehicles drones, time-window penalty costs. verified correctness using Gurobi. In response problem’s characteristics, a hybrid genetic algorithm variable neighborhood search learning mechanism (HGAVNS-LM) proposed solve problem. starts by generating initial population combination logistic mapping reverse learning. It then improves operators optimize population. To improve algorithm’s performance, an individual elite archive used knowledge learning, self-learning established dynamically adjust key parameters. solution obtained HGAVNS-LM shows deviation −0.2% −0.3% compared Gurobi, but it saves 99.68% solving time. Compared algorithm, improvement rates are 5.1% 13.0%, respectively. Through analysis multiple sets test cases, concluded that time-varying networks, different detour rules all affect plans. research results provide more scientific theoretical basis logistics companies customize solutions.

Language: Английский

Citations

3
A fuzzy programming model for decentralization and drone utilization in urban humanitarian relief chains DOI
Amirali Amirsahami, Farnaz Barzinpour, Mir Saman Pishvaee

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2025, Volume and Issue: 195, P. 103949 - 103949

Published: Jan. 20, 2025

Citations

2
Two-echelon multi-depot multi-period location-routing problem with pickup and delivery DOI
Yong Wang, Xiuwen Wang,

Yuanhan Wei

et al.

Computers & Industrial Engineering, Journal Year: 2023, Volume and Issue: 182, P. 109385 - 109385

Published: June 15, 2023

Language: Английский

Citations

24
Collaboration and resource sharing in the multidepot time-dependent vehicle routing problem with time windows DOI
Yong Wang, Zikai Wei, Siyu Luo

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2024, Volume and Issue: 192, P. 103798 - 103798

Published: Sept. 30, 2024

Language: Английский

Citations

13
An efficient pavement distress detection scheme through drone–ground vehicle coordination DOI
Yiyue Zhao, Wei Zhang, Ying Yang

et al.

Transportation Research Part A Policy and Practice, Journal Year: 2024, Volume and Issue: 180, P. 103949 - 103949

Published: Jan. 6, 2024

Language: Английский

Citations

9
Vehicle routing problem with time windows and carbon emissions: a case study in logistics distribution DOI
Ping Lou, Zikang Zhou, Yuhang Zeng

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(29), P. 41600 - 41620

Published: Feb. 7, 2024

Language: Английский

Citations

9