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.
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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