Kangaroo: An Efficient Constraint-Based Local Search System Using Lazy Propagation
نویسندگان
چکیده
In this paper, we introduce Kangaroo, a constraint-based local search system. While existing systems such as Comet maintain invariants after every move, Kangaroo adopts a lazy strategy, updating invariants only when they are needed. Our empirical evaluation shows that Kangaroo consistently has a smaller memory footprint than Comet, and is usually significantly faster.
منابع مشابه
CLP Entailment as Lazy Clause Generation
In this paper we present an algorithm for deciding entailment G |= H of properties G and H defined using Constraint Logic Programming (CLP). The algorithm is based on Satisfiability Modulo Theories (SMT) over a theory derived from the CLP program. The implementation is based on lazy clause generation. Existing methods for discharging such entailments rely on applying a set of proof rules (such ...
متن کاملQingTing: A Fast SAT Solver Using Local Search and Efficient Unit Propagation
In this paper, we present a new SAT solver that combines a recently proposed local search algorithm — unitwalk — with efficient unit propagation techniques. Unlike many other local-search SAT algorithms, unitwalk ’s search relies heavily on unit propagation. In our solver, QingTing, unit propagation is implemented with an efficient unit propagation algorithm using an underlying lazy data struct...
متن کاملInterleaving Constraint Propagation: An Efficient Cooperative Search with Branch and Bound
The main characteristic of any constraint solver is Constraint propagation. Then it is very important to be able to manage constraint propagation as efficiently as possible, we present a hybrid solver based on a Branch and Bound algorithm combined with constraint propagation to reduce the search space. Based on some observations of the solving process constraint propagation is triggered by some...
متن کاملInterval Constraint Solving Using Propositional SAT Solving Techniques
In order to facilitate automated reasoning about large Boolean combinations of non-linear arithmetic constraints involving transcendental functions, we extend the paradigm of lazy theorem proving to intervalbased arithmetic constraint solving. Algorithmically, our approach deviates substantially from “classical” lazy theorem proving approaches in that it directly controls arithmetic constraint ...
متن کاملAnd Tam : Extending Genet with Lazy Arc Consistency 101
| Many important applications, such as graph coloring, scheduling and production planning, can be solved by GENET, a local search method which is used to solve binary constraint satisfaction problems (CSPs). Where complete search methods are typically augmented with consistency methods to reduce the search, local search methods are not. We propose a consistency technique, lazy arc consistency ,...
متن کامل