253 citations · 437 across the 17 of their papers we have counts for
17 papers
Task-Driven Three-Layer Distributed Scheduling for Emergency Earth Observation in Large Low-Earth-Orbit Constellations
Qian Yin, Xinwei Wang, Guohua Wu
Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency requests may arrive after committe…
UAV 3-D path planning based on MOEA/D with adaptive areal weight adjustment
Yougang Xiao, Hao Yang, Huan Liu +2
Unmanned aerial vehicles (UAVs) are desirable platforms for time-efficient and cost-effective task execution. 3-D path planning is a key challenge for task decision-making. This pa…
Performance assessment and exhaustive listing of 500+ nature inspired metaheuristic algorithms
Zhongqiang Ma, Guohua Wu, Ponnuthurai N. Suganthan +2
Metaheuristics are popularly used in various fields, and they have attracted much attention in the scientific and industrial communities. In recent years, the number of new metaheu…
DL-DRL: A double-level deep reinforcement learning approach for large-scale task scheduling of multi-UAV
Xiao Mao, Zhiguang Cao, Mingfeng Fan +2
Exploiting unmanned aerial vehicles (UAVs) to execute tasks is gaining growing popularity recently. To solve the underlying task scheduling problem, the deep reinforcement learning…
Logistics in the Sky: A Two-phase Optimization Approach for the Drone Package Pickup and Delivery System
Fangyu Hong, Guohua Wu, Qizhang Luo +3
The application of drones in the last-mile distribution is a research hotspot in recent years. Different from the previous urban distribution mode that depends on trucks, this pape…
An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem
Bingjie Li, Guohua Wu, Yongming He +2
Vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem, and many models and algorithms have been proposed to solve the VRP and its variants. Althoug…
Curvature Graph Neural Network
Haifeng Li, Jun Cao, Jiawei Zhu +3
Graph neural networks (GNNs) have achieved great success in many graph-based tasks. Much work is dedicated to empowering GNNs with the adaptive locality ability, which enables meas…
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems
Yongming He, Guohua Wu, Yingwu Chen +1
There hardly exists a general solver that is efficient for scheduling problems due to their diversity and complexity. In this study, we develop a two-stage framework, in which rein…
Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks
Haifeng Li, Jun Cao, Jiawei Zhu +2
One of the key problems of GNNs is how to describe the importance of neighbor nodes in the aggregation process for learning node representations. A class of GNNs solves this proble…
Integrating Variable Reduction Strategy with Evolutionary Algorithm for Solving Nonlinear Equations Systems
Aijuan Song, Guohua Wu, Witold Pedrycz
Nonlinear equations systems (NESs) are widely used in real-world problems while they are also difficult to solve due to their characteristics of nonlinearity and multiple roots. Ev…
Bottom-up mechanism and improved contract net protocol for the dynamic task planning of heterogeneous Earth observation resources
Baoju Liu, Min Deng, Guohua Wu +3
Earth observation resources are becoming increasingly indispensable in disaster relief, damage assessment and related domains. Many unpredicted factors, such as the change of obser…
Ensemble of meta-heuristic and exact algorithm based on the divide and conquer framework for multi-satellite observation scheduling
Guohua Wu, Qizhang Luo, Xiao Du +3
Satellite observation scheduling plays a significant role in improving the efficiency of Earth observation systems. To solve the large-scale multi-satellite observation scheduling…
An Autonomous Path Planning Method for Unmanned Aerial Vehicle based on A Tangent Intersection and Target Guidance Strategy
Huan Liu, Xiamiao Li, Mingfeng Fan +3
Unmanned aerial vehicle (UAV) path planning enables UAVs to avoid obstacles and reach the target efficiently. To generate high-quality paths without obstacle collision for UAVs, th…
Agile Earth observation satellite scheduling over 20 years: formulations, methods and future directions
Xinwei Wang, Guohua Wu, Lining Xing +1
Agile satellites with advanced attitude maneuvering capability are the new generation of Earth observation satellites (EOSs). The continuous improvement in satellite technology and…
Simulated annealing based heuristic for multiple agile satellites scheduling under cloud coverage uncertainty
Chao Han, Yi Gu, Guohua Wu +1
Agile satellites are the new generation of Earth observation satellites (EOSs) with stronger attitude maneuvering capability. Since optical remote sensing instruments equipped on s…
An adaptive Simulated Annealing-based satellite observation scheduling method combined with a dynamic task clustering strategy
Guohua Wu, Huilin Wang, Haifeng Li +4
Efficient scheduling is of great significance to rationally make use of scarce satellite resources. Task clustering has been demonstrated to realize an effective strategy to improv…
Across neighbourhood search for numerical optimization
Guohua Wu
Population-based search algorithms (PBSAs), including swarm intelligence algorithms (SIAs) and evolutionary algorithms (EAs), are competitive alternatives for solving complex optim…