Proteus: A Hierarchical Portfolio of Solvers and Transformations

• Published in: Integration of AI and OR Techniques in Constraint Programming pp. 301 - 317
• Main Authors: Hurley, Barry, Kotthoff, Lars, Malitsky, Yuri, O’Sullivan, Barry
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2014
• Series: Lecture Notes in Computer Science
• Subjects: Algorithm Portfolio; Constraint Satisfaction Problem; Constraint Tightness; Direct Encode; Portfolio Approach
• ISBN: 3319070452; 9783319070452
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-07046-9_22

In recent years, portfolio approaches to solving SAT problems and CSPs have become increasingly common. There are also a number of different encodings for representing CSPs as SAT instances. In this paper, we leverage advances in both SAT and CSP solving to present a novel hierarchical portfolio-based approach to CSP solving, which we call Proteus, that does not rely purely on CSP solvers. Instead, it may decide that it is best to encode a CSP problem instance into SAT, selecting an appropriate encoding and a corresponding SAT solver. Our experimental evaluation used an instance of Proteus that involved four CSP solvers, three SAT encodings, and six SAT solvers, evaluated on the most challenging problem instances from the CSP solver competitions, involving global and intensional constraints. We show that significant performance improvements can be achieved by Proteus obtained by exploiting alternative view-points and solvers for combinatorial problem-solving.