Exploiting Functional Constraints in Automatic Dominance Breaking for Constraint Optimization

Authors Jimmy H. M. Lee , Allen Z. Zhong



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Author Details

Jimmy H. M. Lee
  • Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, China
Allen Z. Zhong
  • Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, China

Acknowledgements

We are grateful to the anonymous referees of CP-22 for their useful comments and suggestions.

Cite AsGet BibTex

Jimmy H. M. Lee and Allen Z. Zhong. Exploiting Functional Constraints in Automatic Dominance Breaking for Constraint Optimization. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 31:1-31:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.CP.2022.31

Abstract

Dominance breaking is an effective technique to reduce the time for solving constraint optimization problems. Lee and Zhong propose an automatic dominance breaking framework for a class of constraint optimization problems based on specific forms of objectives and constraints. In this paper, we propose to enhance the framework for problems with nested function calls which can be flattened to functional constraints. In particular, we focus on aggregation functions and exploit such properties as monotonicity, commutativity and associativity to give an efficient procedure for generating effective dominance breaking nogoods. Experimentation also shows orders-of-magnitude runtime speedup using the generated dominance breaking nogoods and demonstrates the ability of our proposal to reveal dominance relations in the literature and discover new dominance relations on problems with ineffective or no known dominance breaking constraints.

Subject Classification

ACM Subject Classification
  • Theory of computation → Constraint and logic programming
Keywords
  • Constraint Optimization Problems
  • Dominance Breaking

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