no code implementations • 6 May 2024 • Yuxuan Wang, Jiongzhi Zheng, Jinyao Xie, Kun He
Similar to MP$_{\text{LS}}$, FIMP-HGA divides the solving into match and partition stages, iteratively refining the solution.
no code implementations • 6 Feb 2024 • Jinghui Xue, Jiongzhi Zheng, Mingming Jin, Kun He
Exact algorithms for MBP mainly follow the branch-and-bound (BnB) framework, whose performance heavily depends on the quality of the upper bound on the cardinality of a maximum s-bundle and the initial lower bound with graph reduction.
no code implementations • 19 Jan 2024 • Jiongzhi Zheng, Zhuo Chen, Chu-min Li, Kun He
In this paper, we propose to transfer the SPB constraint into the clause weighting system of the local search method, leading the algorithm to better solutions.
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 • 24 Jan 2022 • Jiongzhi Zheng, Yawei Hong, Wenchang Xu, Wentao Li, Yongfu Chen
Each iteration of ITSHA consists of an initialization stage and an improvement stage.
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.
no code implementations • 9 Jul 2021 • Jiongzhi Zheng, Jialun Zhong, Menglei Chen, Kun He
In the hybrid algorithm, LKH can help EAX-GA improve the population by its effective local search, and EAX-GA can help LKH escape from local optima by providing high-quality and diverse initial solutions.
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.