Search Results for author: Kaiwen Li

Found 8 papers, 2 papers with code

Learning to Branch in Combinatorial Optimization with Graph Pointer Networks

no code implementations4 Jul 2023 Rui Wang, Zhiming Zhou, Tao Zhang, Ling Wang, Xin Xu, Xiangke Liao, Kaiwen Li

The proposed model, which combines the graph neural network and the pointer mechanism, can effectively map from the solver state to the branching variable decisions.

Combinatorial Optimization Variable Selection

Coevolutionary Framework for Generalized Multimodal Multi-objective Optimization

1 code implementation2 Dec 2022 Wenhua Li, Xingyi Yao, Kaiwen Li, Rui Wang, Tao Zhang, Ling Wang

To address the above two issues, in this study, a novel coevolutionary framework termed CoMMEA for multimodal multi-objective optimization is proposed to better obtain both global and local PSs, and simultaneously, to improve the convergence performance in dealing with high-dimension MMOPs.

Evolutionary Algorithms Transfer Learning

Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization

no code implementations21 Jun 2022 Wei Liu, Rui Wang, Tao Zhang, Kaiwen Li, Wenhua Li, Hisao Ishibuchi

Multi-objective orienteering problems (MO-OPs) are classical multi-objective routing problems and have received a lot of attention in the past decades.

Problem Decomposition reinforcement-learning +1

Deep Reinforcement Learning for Orienteering Problems Based on Decomposition

no code implementations25 Apr 2022 Wei Liu, Tao Zhang, Rui Wang, Kaiwen Li, Wenhua Li, Kang Yang

A dynamic pointer network (DYPN) is introduced as the TSP solver, which takes city locations as inputs and immediately outputs a permutation of nodes.

reinforcement-learning Reinforcement Learning (RL) +1

Deep Reinforcement Learning for Multi-objective Optimization

no code implementations6 Jun 2019 Kaiwen Li, Tao Zhang, Rui Wang

The solutions can be directly obtained by a simple forward calculation of the neural network; thereby, no iteration is required and the MOP can be always solved in a reasonable time.

reinforcement-learning Reinforcement Learning (RL)

Cannot find the paper you are looking for? You can Submit a new open access paper.