1 code implementation • 29 Nov 2022 • Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-min Li, Felip Manyà
In this paper, we propose a local search algorithm for these problems, called BandHS, which applies two multi-armed bandits to guide the search directions when escaping local optima.
1 code implementation • 8 Jul 2022 • Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-min Li
LKH-3 is a powerful extension of LKH that can solve many TSP variants.
no code implementations • 14 Jan 2022 • Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-min Li, Felip Manya
We address Partial MaxSAT (PMS) and Weighted PMS (WPMS), two practical generalizations of the MaxSAT problem, and propose a local search algorithm for these problems, called BandMaxSAT, that applies a multi-armed bandit model to guide the search direction.
1 code implementation • 23 Aug 2021 • Jiongzhi Zheng, Kun He, Jianrong Zhou
In this work, we observe that most local search (W)PMS solvers usually flip a single variable per iteration.
1 code implementation • 8 Dec 2020 • Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-min Li
We address the Traveling Salesman Problem (TSP), a famous NP-hard combinatorial optimization problem.
no code implementations • 22 Jan 2020 • Kun He, Min Zhang, Jianrong Zhou, Yan Jin, Chu-min Li
Inspired by its success in deep learning, we apply the idea of SGD with batch selection of samples to a classic optimization problem in decision version.