Optimizing Multi-Depot Mixed Fleet Vehicle–Drone Routing Under a Carbon Trading Mechanism DOI Creative Commons
Yong Peng, Yanlong Zhang, Dennis Z. Yu

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(24), P. 4023 - 4023

Published: Dec. 22, 2024

The global pursuit of carbon neutrality requires the reduction emissions in logistics and distribution. integration electric vehicles (EVs) drones a collaborative delivery model revolutionizes last-mile by significantly reducing operating costs enhancing efficiency while supporting environmental objectives. This paper presents cost-minimization that addresses transportation, energy, trade within cap-and-trade framework. We develop multi-depot mixed fleet, including fuel vehicles, drone routing optimization model. incorporates key factors such as nonlinear EV charging times, time-dependent travel conditions, energy consumption. propose an adaptive large neighborhood search algorithm integrating spatiotemporal distance (ALNS-STD) to solve this complex introduces five domain-specific operators adjustment mechanism improve solution quality efficiency. Our computational experiments demonstrate effectiveness ALNS-STD, showing its ability optimize routes accounting for both spatial temporal factors. Furthermore, we analyze influence station distribution trading mechanisms on overall route planning, underscoring significance our findings.

Language: Английский

A recent review of solution approaches for green vehicle routing problem and its variants DOI Creative Commons
Annisa Kesy Garside, Noor Azurati Ahmad, Mohd Nabil Muhtazaruddin

et al.

Operations Research Perspectives, Journal Year: 2024, Volume and Issue: 12, P. 100303 - 100303

Published: April 28, 2024

The green vehicle routing problem (GVRP) has been a prominent topic in the literature on logistics and transportation, leading to extensive research previous review studies covering various aspects. Operations seen development of exact approximation approaches for different extensions GVRP. This paper presents an up-to-date thorough GVRP spanning from 2016 2023, encompassing 458 papers. significant contribution lies updated solution algorithms applied both single-objective multi-objective Notably, 92.58% papers introduced mathematical model GVRP, with many researchers adopting mixed integer linear programming as preferred modeling approach. findings indicate that metaheuristics hybrid are most employed addressing Among approaches, combination metaheuristics-metaheuristics is particularly favored by researchers. Furthermore, large neighborhood search (LNS) its variants (especially adaptive search) emerges widely adopted algorithm These proposed within metaheuristic where A-/LNS often combined other algorithms. Conversely, predominant NSGA-II being frequently algorithm. Researchers utilize GAMS CPLEX optimization software solvers. MATLAB commonly language implementing

Language: Английский

Citations

8
Improved Swarm Intelligence-Based Logistics Distribution Optimizer: Decision Support for Multimodal Transportation of Cross-Border E-Commerce DOI Creative Commons
Jiayi Xu, Mario Di Nardo, Shi Yin

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(5), P. 763 - 763

Published: March 4, 2024

Cross-border e-commerce logistics activities increasingly use multimodal transportation modes. In this mode, the of high-performance optimizers to provide decision support for cross-border needs be given attention. This study constructs a distribution optimization model transportation. The mathematical aims minimize costs, carbon emissions during process, and maximize customer satisfaction as objective functions. It also considers constraints from multiple dimensions, such cargo aircraft vehicle load limitations. Meanwhile, corresponding improvement strategies were designed based on Sand Cat Swarm Optimization (SCSO) algorithm. An improved swarm intelligence algorithm was proposed develop an optimizer solving. effectiveness verified through real-world case results indicate that using solution in study, cost delivery can reduced, while improved.

Language: Английский

Citations

7
Scientific mapping and research perspectives of the vehicle routing problem: An approach from sustainability strategies DOI Creative Commons
Paola Alzate, Gabriel Antonio Moyano Londoño,

José Manuel Slater Carrasco

et al.

Sustainable Futures, Journal Year: 2024, Volume and Issue: unknown, P. 100390 - 100390

Published: Nov. 1, 2024

Language: Английский

Citations

1
A novel vehicle path planning method for freight enterprises considering environmental regulation DOI
Xu Zhang, Yingchun Hao,

Xinuo Zhao

et al.

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 423, P. 138839 - 138839

Published: Sept. 12, 2023

Language: Английский

Citations

3
Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles DOI Open Access
Xinhua Gao, Song Liu, Yan Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(6), P. 2357 - 2357

Published: March 12, 2024

In order to achieve the goal of low-carbon, efficient delivery using unmanned vehicles, a multi-objective optimization model considering carbon emissions in problem optimizing multi-route for vehicles is proposed. An improved genetic algorithm (IGA) designed solving this problem. This study takes into account constraints such as maximum service duration delivery, number and approved loading capacity with objective minimizing startup cost, transportation fuel environmental cost terms dioxide vehicles. A combination encoding method based on integer trips, customers used. The inclusion simulated annealing an elite selection strategy design IGA enhances quality efficiency algorithm. international dataset Solomon RC 208 used verify effectiveness small-, medium-, large-scale cases by comparing them (GA) (SA). research results show that proposed applicable while emissions. Compared GA SA, demonstrates faster convergence speed higher efficiency. Additionally, problem’s scale increases, average total deviation rate changes significantly, better solutions are obtained IGA. Furthermore, routes primarily depends their costs distance, choice different vehicle types has impact duration, trips. considers shows 22.6% difference its compared does not consider algorithms provide achieving low-carbon aiming reduce costs. They also contribute development application technology field.

Language: Английский

Citations

0
Solving a real case of rich vehicle routing problem with zone-dependent transportation costs DOI
Rafael Grosso, Jesús Muñuzuri, Alejandro Escudero-Santana

et al.

Central European Journal of Operations Research, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 14, 2024

Language: Английский

Citations

0
Optimizing Multi-Depot Mixed Fleet Vehicle–Drone Routing Under a Carbon Trading Mechanism DOI Creative Commons
Yong Peng, Yanlong Zhang, Dennis Z. Yu

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(24), P. 4023 - 4023

Published: Dec. 22, 2024

The global pursuit of carbon neutrality requires the reduction emissions in logistics and distribution. integration electric vehicles (EVs) drones a collaborative delivery model revolutionizes last-mile by significantly reducing operating costs enhancing efficiency while supporting environmental objectives. This paper presents cost-minimization that addresses transportation, energy, trade within cap-and-trade framework. We develop multi-depot mixed fleet, including fuel vehicles, drone routing optimization model. incorporates key factors such as nonlinear EV charging times, time-dependent travel conditions, energy consumption. propose an adaptive large neighborhood search algorithm integrating spatiotemporal distance (ALNS-STD) to solve this complex introduces five domain-specific operators adjustment mechanism improve solution quality efficiency. Our computational experiments demonstrate effectiveness ALNS-STD, showing its ability optimize routes accounting for both spatial temporal factors. Furthermore, we analyze influence station distribution trading mechanisms on overall route planning, underscoring significance our findings.

Language: Английский

Citations

0