מיכאל קודיש

אקדמי בכיר

Lazy clause generation in retrospect

Olga Ohrimenko, Peter J. Stuckey, Michael Codish

Lazy clause generation (LCG) is an approach to building constraint programming (CP) solvers that uses ideas from Boolean Satisfiability (SAT) solvers. Propagation in the CP solver is extended to explain itself, lazily creating explanation clauses. This allows SAT style conflict analysis to be used to create clausal nogoods that record the reason for failure, and avoid the same failure in the future. LCG has proven to be a highly effective architecture, used in all most performant CP solvers. In this review we consider how LCG has been refined and expanded over the years since its invention.

שפת פרסום אנגלית
כתב עת Constraints

Keywords

Discrete optimisation
Nogood learning
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ASJC Scopus subject areas

Software
Discrete Mathematics and Combinatorics
Computational Theory and Mathematics
Artificial Intelligence
גישה למסמך
10.1007/s10601-026-09390-9
קבצים וקישורים אחרים
Link to publication in Scopus