Open AccessGlobal constraints in modeling and solving problems within the Constraint Programming paradigm.
Author(s) -
Yu.A. Oleynik,
Alexander Zuenko
Publication year - 2020
Publication title -
trudy kolʹskogo naučnogo centra ran
Language(s) - English
Resource type - Journals
ISSN - 2307-5252
DOI - 10.37614/2307-5252.2020.8.11.006
Subject(s) - constraint programming , computer science , constraint (computer aided design) , task (project management) , set (abstract data type) , constraint satisfaction , mathematical optimization , constraint logic programming , programming paradigm , inductive programming , theoretical computer science , artificial intelligence , mathematics , stochastic programming , programming language , systems engineering , engineering , geometry , probabilistic logic
At the moment, constraint programming technology is a powerful tool for solving combinatorial search and combinatorial optimization problems. To use this technology, any task must be formulated as a task of satisfying constraints. The role of the concept of global constraints in modeling and solving applied problems within the framework of the constraint programming paradigm can hardly be overestimated. The procedures that implement the algorithms of filtering global constraints are the elementary “building blocks” from which the model of a specific applied problem is built. Algorithms for filtering global constraints, as a rule, are supported by the corresponding developed theories that allow organizing high-performance computing. The choice of a particular software library is primarily determined by the extent to which the set and method of implementing global constraints corresponds tothe level of modern research in this area. The main focus of this article is focused on an overview of global constraints that are implemented within the most popular constraint programming libraries: Choco, GeCode, JaCoP, MiniZinc.