Chu Min Li

Dr. Chu Min Li


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 October 2007 in Journal of Artificial Intelligence Research
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Journal Article
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CLChu Min Li
Chu Min Li
FMFelip Manyà
Felip Manyà
JPJ. Planes
J. Planes
Exact Max-SAT solvers, compared with SAT solvers, apply little inference at each node of the proof tree. Commonly used SAT inference rules like unit propagation produce a simplified formula that preserves satisfiability but, unfortunately, solving the Max-SAT problem for the simplified formula is not equivalent to solving it for the original formula. In this paper, we define a number of original inference rules that, besides being applied efficiently, transform Max-SAT instances into equivalent Max-SAT instances which are easier to solve. The soundness of the rules, that can be seen as refinements of unit resolution adapted to Max-SAT, are proved in a novel and simple way via an integer programming transformation. With the aim of finding out how powerful the inference rules are in practice, we have developed a new Max-SAT solver, called MaxSatz, which incorporates those rules, and performed an experimental investigation. The results provide empirical evidence that MaxSatz is very competitive, at least, on random Max-2SAT, random Max-3SAT, Max-Cut, and Graph 3-coloring instances, as well as on the benchmarks from the Max-SAT Evaluation 2006.

1 January 2018 in INFORMS Journal on Computing
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Journal Article
Closed access
CLChu Min Li
Chu Min Li
ZFZhiwen Fang
Zhiwen Fang
HJHua Jiang
Hua Jiang
KXKe Xu
Ke Xu
The maximum clique problem (MaxClique for short) consists of searching for a maximum complete subgraph in a graph. A branch-and-bound (BnB) MaxClique algorithm computes an upper bound of the number of vertices of a maximum clique at every search tree node, to prune the subtree rooted at the node. Existing upper bounds are usually computed from scratch at every search tree node. In this paper, we define an incremental upper bound, called IncUB, which is derived efficiently from previous searches instead of from scratch. Then, we describe a new BnB MaxClique algorithm, called IncMC2, which uses graph coloring and MaxSAT reasoning to filter out the vertices that do not need to be branched on, and uses IncUB to prune the remaining branches. Our experimental results show that IncMC2 is significantly faster than algorithms such as BBMC and IncMaxCLQ. Finally, we carry out experiments to provide evidence that the performance of IncMC2 is due to IncUB. The online supplement is available at https://doi.org/10.1287/ijoc.2017.0770 .

24 July 2010 in Constraints
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Journal Article
Closed access
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CLChu Min Li
Chu Min Li
FMFelip Manyà
Felip Manyà
NMNouredine Ould Mohamedou
Nouredine Ould Mohamedou
JPJordi Planes
Jordi Planes

1 January 2021 in Computers & Operations Research
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Journal Article
Closed access
CBChristian Blum
Christian Blum
MDMarko Djukanovic
Marko Djukanovic
ASAlberto Santini
Alberto Santini
HJHua Jiang
Hua Jiang
CLChu Min Li
Chu Min Li
GRGünter R. Raidl
Günter R. Raidl

1 August 2003 in Discrete Applied Mathematics
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Journal Article
Closed access
CLChu Min Li
Chu Min Li

1 October 2018 in European Journal of Operational Research
Verified
Journal Article
Closed access
CLChu Min Li
Chu Min Li
YLYanli Liu
Yanli Liu
HJHua Jiang
Hua Jiang
FMFelip Manyà
Felip Manyà
YLYu Li
Yu Li