151 citations · 250 across the 7 of their papers we have counts for
7 papers
Learning to Sample in Variable Neighborhood Search Algorithm for Urban Cable Routing Optimization
Wei Liu, Rui Wang, Chenhui Lin +3
Urban underground cable construction is essential for enhancing power grid reliability, yet the high construction costs demand systematic optimization. Constrained by road network…
PlatMetaX: An Integrated MATLAB platform for Meta-Black-Box Optimization
Xu Yang, Rui Wang, Kaiwen Li +3
The landscape of optimization problems has become increasingly complex, necessitating the development of advanced optimization techniques. Meta-Black-Box Optimization (MetaBBO), wh…
Coevolutionary Framework for Generalized Multimodal Multi-objective Optimization
Wenhua Li, Xingyi Yao, Kaiwen Li +3
Most multimodal multi-objective evolutionary algorithms (MMEAs) aim to find all global Pareto optimal sets (PSs) for a multimodal multi-objective optimization problem (MMOP). Howev…
Large-scale matrix optimization based multi microgrid topology design with a constrained differential evolution algorithm
Wenhua Li, Shengjun Huang, Tao Zhang +2
Binary matrix optimization commonly arise in the real world, e.g., multi-microgrid network structure design problem (MGNSDP), which is to minimize the total length of the power sup…
Multimodal Multi-objective Optimization: Comparative Study of the State-of-the-Art
Wenhua Li, Tao Zhang, Rui Wang +1
Multimodal multi-objective problems (MMOPs) commonly arise in real-world problems where distant solutions in decision space correspond to very similar objective values. To obtain a…
Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization
Wei Liu, Rui Wang, Tao Zhang +3
Multi-objective orienteering problems (MO-OPs) are classical multi-objective routing problems and have received a lot of attention in the past decades. This study seeks to solve MO…
Deep Reinforcement Learning for Orienteering Problems Based on Decomposition
Wei Liu, Tao Zhang, Rui Wang +3
This paper presents a new method for solving an orienteering problem (OP) by breaking it down into two parts: a knapsack problem (KP) and a traveling salesman problem (TSP). A KP s…