6 Papers
Yuxuan Sun is an academic researcher from Kunming University of Science and Technology. The author has contributed to research in topics: Computer science & Vehicle routing problem. The author has an hindex of 1, co-authored 2 publications.
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Papers
UAV Stocktaking Task-Planning for Industrial Warehouses Based on the Improved Hybrid Differential Evolution Algorithm
TL;DR: A hybrid Differential Evolution algorithm based on the Lion Swarm Optimization is proposed to conduct regular inventory of finished products and raw and auxiliary materials and a task planning model for UAV inventory library equipped with RFID reader is proposed.
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Study on the optimization of urban emergency supplies distribution paths for epidemic outbreaks
TL;DR: In this article , a multi-objective mathematical model of emergency supplies distribution for large cities in case of an epidemic outbreak is presented, and a hybrid multi-verse optimizer algorithm based on differential evolution (DE-IMOV) is proposed.
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Three-Dimensional Mountain Complex Terrain and Heterogeneous Multi-UAV Cooperative Combat Mission Planning
TL;DR: A heterogeneous multi-UAV cooperative mission planning method in the complex three-dimensional (3D) mountain environment based on the Life-cycle Swarm Optimization (LSO) algorithm, which has good approximation and high convergence accuracy, and it was effectively utilized in the planning of UAV collaborative missions in 3D complex terrain environments.
Density Coverage-Based Exemplar Selection for Incremental SAR Automatic Target Recognition
TL;DR: Zhang et al. as mentioned in this paper proposed a density coverage-based exemplar selection (DCBES) method to choose the key samples of the old class, where the metric learning theory is used to measure the similarity between samples and to obtain the density range of samples.
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A Multi-View SAR ATR Optimal Observation Path Planning Method
Xindi Yu,Jifang Pei,Yuxuan Sun,Weibo Huo,Yulin Huang,Yin Zhang,Jian Yang +6 more
- 17 Jul 2022
TL;DR: Experimental results based on the moving and stationary target acquisition and recognition (MSTAR) dataset have shown that the proposed method obtains superiority in optimal observation path planning.