A survey on vehicle–drone cooperative delivery operations optimization: Models, methods, and future research directions

IF 8.2 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jing Zhou , Jin Yi , Zhenyu Yang , Huayan Pu , Xinyu Li , Jun Luo , Liang Gao
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引用次数: 0

Abstract

With the rise of technology and market demand, unmanned devices, particularly drones, are increasingly used in logistics due to their speed and cost-efficiency. However, the persistence of limiting factors such as battery life and payload capacity has rendered vehicle-drone cooperative delivery an emerging and promising research area. This paper compiles relevant literature on the cooperative operation of vehicles and drones, summarizing key research directions, which encompass a novel classification framework, commonly utilized mathematical models, and solutions. Additionally, we collected algorithmic test cases employed in current research. Finally, the paper analyzes the current research status and the existing challenges and provides suggestions for future research directions.
车辆-无人机合作配送运营优化调查:模型、方法和未来研究方向
随着技术的发展和市场需求的增加,无人设备,尤其是无人机,因其速度快、成本效益高而越来越多地应用于物流领域。然而,由于电池寿命和有效载荷能力等限制因素的持续存在,车辆与无人机的合作配送成为一个新兴且前景广阔的研究领域。本文汇编了车辆与无人机合作运行的相关文献,总结了主要研究方向,其中包括新颖的分类框架、常用的数学模型和解决方案。此外,我们还收集了当前研究中使用的算法测试案例。最后,本文分析了当前的研究现状和存在的挑战,并对未来的研究方向提出了建议。
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来源期刊
Swarm and Evolutionary Computation
Swarm and Evolutionary Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
16.00
自引率
12.00%
发文量
169
期刊介绍: Swarm and Evolutionary Computation is a pioneering peer-reviewed journal focused on the latest research and advancements in nature-inspired intelligent computation using swarm and evolutionary algorithms. It covers theoretical, experimental, and practical aspects of these paradigms and their hybrids, promoting interdisciplinary research. The journal prioritizes the publication of high-quality, original articles that push the boundaries of evolutionary computation and swarm intelligence. Additionally, it welcomes survey papers on current topics and novel applications. Topics of interest include but are not limited to: Genetic Algorithms, and Genetic Programming, Evolution Strategies, and Evolutionary Programming, Differential Evolution, Artificial Immune Systems, Particle Swarms, Ant Colony, Bacterial Foraging, Artificial Bees, Fireflies Algorithm, Harmony Search, Artificial Life, Digital Organisms, Estimation of Distribution Algorithms, Stochastic Diffusion Search, Quantum Computing, Nano Computing, Membrane Computing, Human-centric Computing, Hybridization of Algorithms, Memetic Computing, Autonomic Computing, Self-organizing systems, Combinatorial, Discrete, Binary, Constrained, Multi-objective, Multi-modal, Dynamic, and Large-scale Optimization.
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