A Review of Literature on Vehicle Routing Problems of Last-Mile Delivery in Urban Areas DOI Creative Commons
Reza Jazemi, Ensieh Alidadiani, Kwangseog Ahn

et al.

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(24), P. 13015 - 13015

Published: Dec. 6, 2023

Logistics has long been important in an industrial society. Compared with the traditional structure of distribution, which requires freight to be delivered mostly warehouses or retail stores, customers now often prefer packages their residences, especially after delivery challenges during COVID-19 pandemic. The parcels urban residential areas increases challenge due amount volume, tight schedules, and continuously changing conditions. Last-mile tries address challenges, taking advantage available automation, sensor communication technologies, people’s attitudes toward parcel for benefit all stakeholders. Various approaches last-mile have proposed analyzed literature. This paper reviews recent literature on vehicle routing delivery. review identified four major categories: crowdshipping, lockers, by sidekicks, optional points. nature problems is discussed five aspects: fleet capacity, time window, option, dynamism input, stochastic parameters. identifies achievements limitations research proposes a future agenda.

Language: Английский

Multi-objective evolutionary approach based on K-means clustering for home health care routing and scheduling problem DOI Creative Commons
Mariem Belhor, Adnen El Amraoui, Abderrazak Jemai

et al.

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 213, P. 119035 - 119035

Published: Oct. 17, 2022

Language: Английский

Citations

43
A robust algorithm based on Differential Evolution with local search for the Capacitated Vehicle Routing Problem DOI
Israel Pereira de Souza, Maria Claudia Silva Bóeres, Renato Elias Nunes de Moraes

et al.

Swarm and Evolutionary Computation, Journal Year: 2023, Volume and Issue: 77, P. 101245 - 101245

Published: Jan. 14, 2023

Language: Английский

Citations

33
Enhancing Reliability Calculation for One-Output k-out-of-n Binary-state Networks Using a New BAT DOI
Wei‐Chang Yeh

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: 257, P. 110835 - 110835

Published: Jan. 15, 2025

Language: Английский

Citations

1
FLDQN: Cooperative Multi-Agent Federated Reinforcement Learning for Solving Travel Time Minimization Problems in Dynamic Environments Using SUMO Simulation DOI Creative Commons

Abdul Wahab Mamond,

Majid Kundroo, Seong-eun Yoo

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(3), P. 911 - 911

Published: Feb. 3, 2025

The increasing volume of traffic has led to severe challenges, including congestion, heightened energy consumption, increased air pollution, and prolonged travel times. Addressing these issues requires innovative approaches for optimizing road network utilization. While Deep Reinforcement Learning (DRL)-based methods have shown remarkable effectiveness in dynamic scenarios like management, their primary focus been on single-agent setups, limiting applicability real-world multi-agent systems. Managing agents fostering collaboration a reinforcement learning scenario remains challenging task. This paper introduces cooperative federated algorithm named FLDQN address the challenge agent cooperation by solving time minimization challenges (MARL) scenarios. leverages facilitate knowledge sharing among intelligent agents, vehicle routing reducing congestion environments. Using SUMO simulator, multiple equipped with deep Q-learning models interact local environments, share model updates via server, collectively enhance policies using unique observations while benefiting from collective experiences other agents. Experimental evaluations demonstrate that achieves significant average reduction over 34.6% compared non-cooperative simultaneously lowering computational overhead through distributed learning. underscores vital impact provides an solution enabling environment.

Language: Английский

Citations

1
A mixed closed-open multi-depot routing and scheduling problem for homemade meal delivery incorporating drone and crowd-sourced fleet: A self-adaptive hyper-heuristic approach DOI
Mahdi Hamid, Mohammad Mahdi Nasiri, Masoud Rabbani

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 120, P. 105876 - 105876

Published: Jan. 28, 2023

Language: Английский

Citations

16
The vehicle routing problem in the last decade: variants, taxonomy and metaheuristics DOI Open Access

Said Elatar,

Karim Abouelmehdi, Mohammed Essaid Riffi

et al.

Procedia Computer Science, Journal Year: 2023, Volume and Issue: 220, P. 398 - 404

Published: Jan. 1, 2023

Vehicle routing problem is a NP-hard and combinatorial optimization problem; it appeared first time in 1959 the paper of mathematician Dantzig. The goal VRP to locate optimal routes some vehicles that begin from depot serve each customer one then return (i.e., Starting point). From its beginning, research literature this area growing rapidly causing extension many variants for making real-world problem. For solving it, researchers have tried firstly exact methods heuristics lastly metaheuristics. This aims targets instance: (i) discovering evolution over last decade; (ii) knowing trends, challenges opportunities next years fields by discovering, comparing recent reviews papers related either or metaheuristics exploiting these results building on them other papers.

Language: Английский

Citations

12
A Bibliometric Visualized Analysis and Classification of Vehicle Routing Problem Research DOI Open Access

Qiuping Ni,

Yuanxiang Tang

Sustainability, Journal Year: 2023, Volume and Issue: 15(9), P. 7394 - 7394

Published: April 29, 2023

The vehicle routing problem (VRP), as a classic combinatorial optimization problem, has always been hot research topic in operations research. In order to gain deeper understanding of the VRP this work uses knowledge graph comprehensively analyze and summarize literature related from 1959 2022 Web Science (WoS) database. Firstly, according basic statistical information literature, annual publications, authors, their institutions countries, keyword co-occurrence, co-citation network are analyzed generalize on predict its future development trend. results show that, past 60 years, there have abundant changes VRP. United States China made most important contributions field According WoS retrieval classification methods, models solutions classified, model solving algorithms divided into exact algorithms, heuristic metaheuristic hyper-heuristic machine learning, etc. that computing technology plays an role dynamic VRP, deep reinforcement directions optimization. can provide help guidance for beginners scholars outside industry understand hotspots

Language: Английский

Citations

12
Integrating Machine Learning Into Vehicle Routing Problem: Methods and Applications DOI Creative Commons
Reza Shahbazian, Luigi Di Puglia Pugliese, Francesca Guerriero

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 93087 - 93115

Published: Jan. 1, 2024

The vehicle routing problem (VRP) and its variants have been intensively studied by the operational research community. existing surveys majority of published articles tackle traditional solutions, including exact methods, heuristics, meta-heuristics. Recently, machine learning (ML)-based methods applied to a variety combinatorial optimization problems, specifically VRPs. strong trend using ML in VRPs gap literature motivated us review state-of-the-art. To provide clear understanding ML-VRP landscape, we categorize related studies based on their applications/constraints technical details. We mainly focus reinforcement (RL)-based approaches because importance literature, while also address non RL-based methods. cover both theoretical practical aspects clearly addressing trends, gap, limitations advantages ML-based discuss some potential future directions.

Language: Английский

Citations

4
Multi-task differential evolution algorithm with dynamic resource allocation: A study on e-waste recycling vehicle routing problem DOI
Ying Hou, Yanjie Shen, Honggui Han

et al.

Swarm and Evolutionary Computation, Journal Year: 2025, Volume and Issue: 92, P. 101806 - 101806

Published: Jan. 2, 2025

Language: Английский

Citations

0
Green Vehicle Routing Problem Optimization for LPG Distribution: Genetic Algorithms for Complex Constraints and Emission Reduction DOI Open Access
Nur Indrianti, Raden Achmad Chairdino Leuveano, Salwa Hanim Abdul‐Rashid

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(3), P. 1144 - 1144

Published: Jan. 30, 2025

This study develops a Green Vehicle Routing Problem (GVRP) model to address key logistics challenges, including time windows, simultaneous pickup and delivery, heterogeneous vehicle fleets, multiple trip allocations. The incorporates emissions-related costs, such as carbon taxes, encourage sustainable supply chain operations. Emissions are calculated based on the total shipment weight travel distance of each vehicle. objective is minimize operational costs while balancing economic efficiency environmental sustainability. A Genetic Algorithm (GA) applied optimize routing allocation, enhancing reducing costs. Liquid Petroleum Gas (LPG) distribution case in Yogyakarta, Indonesia, validates model’s effectiveness. results show significant cost savings compared current route planning methods, alongside slight increase carbon. sensitivity analysis was conducted by testing with varying numbers stations, revealing its robustness impact station density solution quality. By integrating taxes detailed emission calculations into function, GVRP offers practical for real-world challenges. provides valuable insights achieving cost-effective operations advancing green practices.

Language: Английский

Citations

0