3 Search Results for "Luo, Chuan"

Document
DOI: 10.4230/LIPIcs.CP.2023.12
Towards More Efficient Local Search for Pseudo-Boolean Optimization

Authors: Yi Chu, Shaowei Cai, Chuan Luo, Zhendong Lei, and Cong Peng

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
Pseudo-Boolean (PB) constraints are highly expressive, and many combinatorial optimization problems can be modeled using pseudo-Boolean optimization (PBO). It is recognized that stochastic local search (SLS) is a powerful paradigm for solving combinatorial optimization problems, but the development of SLS for solving PBO is still in its infancy. In this paper, we develop an effective SLS algorithm for solving PBO, dubbed NuPBO, which introduces a novel scoring function for PB constraints and a new weighting scheme. We conduct experiments on a broad range of six public benchmarks, including three real-world benchmarks, a benchmark from PB competition, an integer linear programming optimization benchmark, and a crafted combinatorial benchmark, to compare NuPBO against five state-of-the-art competitors, including a recently-proposed SLS PBO solver LS-PBO, two complete PB solvers PBO-IHS and RoundingSat, and two mixed integer programming (MIP) solvers Gurobi and SCIP. NuPBO has been exhibited to perform best on these three real-world benchmarks. On the other three benchmarks, NuPBO shows competitive performance compared to state-of-the-art competitors, and it significantly outperforms LS-PBO, indicating that NuPBO greatly advances the state of the art in SLS for solving PBO.
Cite as

Yi Chu, Shaowei Cai, Chuan Luo, Zhendong Lei, and Cong Peng. Towards More Efficient Local Search for Pseudo-Boolean Optimization. In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 12:1-12:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{chu_et_al:LIPIcs.CP.2023.12,
  author =	{Chu, Yi and Cai, Shaowei and Luo, Chuan and Lei, Zhendong and Peng, Cong},
  title =	{{Towards More Efficient Local Search for Pseudo-Boolean Optimization}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{12:1--12:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.12},
  URN =		{urn:nbn:de:0030-drops-190490},
  doi =		{10.4230/LIPIcs.CP.2023.12},
  annote =	{Keywords: Pseudo-Boolean Optimization, Stochastic Local Search, Scoring Function, Weighting Scheme}
}
Document
DOI: 10.4230/LIPIcs.SEA.2023.10
Solving Directed Feedback Vertex Set by Iterative Reduction to Vertex Cover

Authors: Sebastian Angrick, Ben Bals, Katrin Casel, Sarel Cohen, Tobias Friedrich, Niko Hastrich, Theresa Hradilak, Davis Issac, Otto Kißig, Jonas Schmidt, and Leo Wendt

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
In the Directed Feedback Vertex Set (DFVS) problem, one is given a directed graph G = (V,E) and wants to find a minimum cardinality set S ⊆ V such that G-S is acyclic. DFVS is a fundamental problem in computer science and finds applications in areas such as deadlock detection. The problem was the subject of the 2022 PACE coding challenge. We develop a novel exact algorithm for the problem that is tailored to perform well on instances that are mostly bi-directed. For such instances, we adapt techniques from the well-researched vertex cover problem. Our core idea is an iterative reduction to vertex cover. To this end, we also develop a new reduction rule that reduces the number of not bi-directed edges. With the resulting algorithm, we were able to win third place in the exact track of the PACE challenge. We perform computational experiments and compare the running time to other exact algorithms, in particular to the winning algorithm in PACE. Our experiments show that we outpace the other algorithms on instances that have a low density of uni-directed edges.
Cite as

Sebastian Angrick, Ben Bals, Katrin Casel, Sarel Cohen, Tobias Friedrich, Niko Hastrich, Theresa Hradilak, Davis Issac, Otto Kißig, Jonas Schmidt, and Leo Wendt. Solving Directed Feedback Vertex Set by Iterative Reduction to Vertex Cover. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 10:1-10:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{angrick_et_al:LIPIcs.SEA.2023.10,
  author =	{Angrick, Sebastian and Bals, Ben and Casel, Katrin and Cohen, Sarel and Friedrich, Tobias and Hastrich, Niko and Hradilak, Theresa and Issac, Davis and Ki{\ss}ig, Otto and Schmidt, Jonas and Wendt, Leo},
  title =	{{Solving Directed Feedback Vertex Set by Iterative Reduction to Vertex Cover}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{10:1--10:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.10},
  URN =		{urn:nbn:de:0030-drops-183602},
  doi =		{10.4230/LIPIcs.SEA.2023.10},
  annote =	{Keywords: directed feedback vertex set, vertex cover, reduction rules}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.CP.2021.5
Improving Local Search for Structured SAT Formulas via Unit Propagation Based Construct and Cut Initialization (Short Paper)

Authors: Shaowei Cai, Chuan Luo, Xindi Zhang, and Jian Zhang

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
This work is dedicated to improving local search solvers for the Boolean satisfiability (SAT) problem on structured instances. We propose a construct-and-cut (CnC) algorithm based on unit propagation, which is used to produce initial assignments for local search. We integrate our CnC initialization procedure within several state-of-the-art local search SAT solvers, and obtain the improved solvers. Experiments are carried out with a benchmark encoded from a spectrum repacking project as well as benchmarks encoded from two important mathematical problems namely Boolean Pythagorean Triple and Schur Number Five. The experiments show that the CnC initialization improves the local search solvers, leading to better performance than state-of-the-art SAT solvers based on Conflict Driven Clause Learning (CDCL) solvers.
Cite as

Shaowei Cai, Chuan Luo, Xindi Zhang, and Jian Zhang. Improving Local Search for Structured SAT Formulas via Unit Propagation Based Construct and Cut Initialization (Short Paper). In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 5:1-5:10, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@InProceedings{cai_et_al:LIPIcs.CP.2021.5,
  author =	{Cai, Shaowei and Luo, Chuan and Zhang, Xindi and Zhang, Jian},
  title =	{{Improving Local Search for Structured SAT Formulas via Unit Propagation Based Construct and Cut Initialization}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{5:1--5:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.5},
  URN =		{urn:nbn:de:0030-drops-152969},
  doi =		{10.4230/LIPIcs.CP.2021.5},
  annote =	{Keywords: Satisfiability, Local Search, Unit Propagation, Mathematical Problems}
}
  • Refine by Author
  • 2 Cai, Shaowei
  • 2 Luo, Chuan
  • 1 Angrick, Sebastian
  • 1 Bals, Ben
  • 1 Casel, Katrin
  • Show More...

  • Refine by Classification
  • 2 Theory of computation → Randomized local search
  • 1 Mathematics of computing → Graph algorithms

  • Refine by Keyword
  • 1 Local Search
  • 1 Mathematical Problems
  • 1 Pseudo-Boolean Optimization
  • 1 Satisfiability
  • 1 Scoring Function
  • Show More...

  • Refine by Type
  • 3 document

  • Refine by Publication Year
  • 2 2023
  • 1 2021

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023 Schloss Dagstuhl - LZI GmbH Imprint Privacy Contact