22 citations · 24 across the 3 of their papers we have counts for
7 papers
A Hierarchical Destroy and Repair Approach for Solving Very Large-Scale Travelling Salesman Problem
Zhang-Hua Fu, Sipeng Sun, Jintong Ren +6
For prohibitively large-scale Travelling Salesman Problems (TSPs), existing algorithms face big challenges in terms of both computational efficiency and solution quality. To addres…
Efficient Training of Multi-task Neural Solver for Combinatorial Optimization
Chenguang Wang, Zhang-Hua Fu, Pinyan Lu +1
Efficiently training a multi-task neural solver for various combinatorial optimization problems (COPs) has been less studied so far. Naive application of conventional multi-task le…
A Partition-and-Merge Algorithm for Solving the Steiner Tree Problem in Large Graphs
Ming Sun, Xinyu Wu, Yi Zhou +2
The Steiner tree problem aims to determine a minimum edge-weighted tree that spans a given set of terminal vertices from a given graph. In the past decade, a considerable number of…
Learning to Detect Critical Nodes in Sparse Graphs via Feature Importance Awareness
Xuwei Tan, Yangming Zhou, MengChu Zhou +1
Detecting critical nodes in sparse graphs is important in a variety of application domains, such as network vulnerability assessment, epidemic control, and drug design. The critica…
An effective hybrid search algorithm for the multiple traveling repairman problem with profits
Jintong Ren, Jin-Kao Hao, Feng Wu +1
As an extension of the traveling repairman problem with profits, the multiple traveling repairman problem with profits consists of multiple repairmen who visit a subset of all cust…
Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances
Zhang-Hua Fu, Kai-Bin Qiu, Hongyuan Zha
For the traveling salesman problem (TSP), the existing supervised learning based algorithms suffer seriously from the lack of generalization ability. To overcome this drawback, thi…