Constraint Networks

Abstract

Constraint Programming (CP) is a useful technology for modeling and solving combinatorial constrained problems. On the one hand, on can use a library like PyCSP 3 for easily modeling problems arising in various application fields (e.g., scheduling, planning, data-mining, cryptography, bio-informatics, organic chemistry, etc.). Problem instances can then be directly generated from specific models and data. On the other hand, for solving instances (notably, represented in XCSP 3 format), one can use a constraint solver like ACE, which is presented in this paper.ACE is an open-source constraint solver, developed in Java, which focuses on integer variables (including 0/1-Boolean variables), state-of-the-art table constraints, popular global constraints, search heuristics and (mono-criterion) optimization. Constraints over Integer Variables Generic Constraints Constraint intension Constraint extension Language-based Constraints Constraint regular Constraint mdd Comparison-based Constraints Constraints allDifferent, allDifferentList, allEqual Constraints increasing, decreasing Constraints lexIncreasing, lexDecreasing Constraint precedence Counting Constraints Constraint sum Constraint count Constraint nValues Constraint cardinality Connection Constraints Constraints maximum and maximumArg Constraints minimum and minimumArg Constraint element and channel Packing and Scheduling Constraints

Improving GAC-4 for Table and MDD Constraints

“…Solver: or-tools 3158. Selected Benchmarks: all problems can be downloaded from the Solver Competition archive [13]. We selected problems having only positive table constraints and at least one variable whose domain is not Boolean.…”

Value Ordering for Finding All Solutions: Interactions with Adaptive Variable Ordering

“…AC-3 was used as its arc consistency component which was equipped with the residual support mechanism and revision condition [7]. We conducted experiments with the static versions of min-conflict, max-conflict, cruciality, anticruciality, promise and anti-promise value ordering heuristics.…”

Comparison of the Inaccurate Data Representations in the Subdefinite Models

“…Задача удовлетворения ограничений может быть сформулирована с различной степенью детализации [3,9,10]. Далее в статье будем использовать следующие определения:…”