• Constraints (IF 1.106) Pub Date : 2020-02-06
Gilles Audemard, Frédéric Boussemart, Christophe Lecoutre, Cédric Piette, Olivier Roussel

In this paper, we present a summary of XCSP3, together with its ecosystem. XCSP3 is a format used to build integrated representations of combinatorial constrained problems. Interestingly, XCSP3 preserves the structure of models, by handling arrays of variables and groups/blocks of constraints, which makes it rather unique in the literature. Furthermore, the ecosystem of XCSP3 is well supplied: it includes

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2020-01-15
Jaime E. González, Andre A. Cire, Andrea Lodi, Louis-Martin Rousseau

We propose an optimization framework which integrates decision diagrams (DDs) and integer linear programming (ILP) to solve combinatorial optimization problems. The hybrid DD-ILP approach explores the solution space based on a recursive compilation of relaxed DDs and incorporates ILP calls to solve subproblems associated with DD nodes. The selection of DD nodes to be explored by ILP technology is a

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-12-20
Mohamed Amine Omrani, Wady Naanaa

Although graphs are widely used to encode and solve various computational problems, little research exists on constrained graph construction. The current research was carried out to shed light on the problem of generating graphs, where the construction process is guided by various structural restrictions, like vertex degrees, proximity among vertices, and imposed and forbidden patterns. The main contribution

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-12-26
Kuldeep S. Meel, Aditya A. Shrotri, Moshe Y. Vardi

The problem of counting the number of solutions of a DNF formula, also called #DNF, is a fundamental problem in artificial intelligence with applications in diverse domains ranging from network reliability to probabilistic databases. Owing to the intractability of the exact variant, efforts have focused on the design of approximate techniques for #DNF. Consequently, several Fully Polynomial Randomized

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-08-20
Vadim Levit, Zohar Komarovsky, Tal Grinshpoun, Ana L. C. Bazzan, Amnon Meisels

Search for equilibria in games is a hard problem and many games do not have a pure Nash equilibrium (PNE). Incentive mechanisms have been shown to secure a PNE in certain families of games. The present study utilizes the similarity between Asymmetric Distributed Constraints Optimization Problems (ADCOPs) and games, to construct search algorithms for finding outcomes and incentives that secure a pure

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-04-05
Michał Karpiński, Marek Piotrów

Boolean cardinality constraints (CCs) state that at most (at least, or exactly) k out of n propositional literals can be true. We propose a new, arc-consistent, easy to implement and efficient encoding of CCs based on a new class of selection networks. Several comparator networks have been recently proposed for encoding CCs and experiments have proved their efficiency (Abío et al. 2013, Asín et al

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-08-07
Anthony Palmieri, Arnaud Lallouet, Luc Pons

Software Defined Networking (or SDN) allows to apply a centralized control over a network of commuters in order to provide better global performances. One of the problem to solve is the multicommodity flow routing where a set of demands have to be routed at minimum cost. In contrast with other versions of this problem, we consider here problems with congestion that change the cost of a link according

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-02-19
Vinasetan Ratheil Houndji, Pierre Schaus, Laurence Wolsey

In a previous work we introduced a global StockingCost constraint to compute the total number of periods between the production periods and the due dates in a multi-order capacitated lot-sizing problem. Here we consider a more general case in which each order can have a different per period stocking cost and the goal is to minimise the total stocking cost. In addition the production capacity, limiting

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-02-08
Dimitris Achlioptas, Panos Theodoropoulos

The idea of counting the number of satisfying truth assignments (models) of a formula by adding random parity constraints can be traced back to the seminal work of Valiant and Vazirani showing that NP is as easy as detecting unique solutions. While theoretically sound, the random parity constraints used in that construction suffer from the following drawback: each constraint, on average, involves half

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2019-01-12
Aolong Zha, Miyuki Koshimura, Hiroshi Fujita

Many combinatorial problems in various fields can be translated to Maximum Satisfiability (MaxSAT) problems. Although the general problem is $$\mathcal {N}\mathcal {P}$$-hard, more and more practical problems may be solved due to the significant effort which has been devoted to the development of efficient solvers. The art of constraints encoding is as important as the art of devising algorithms for

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-11-09
Diego de Uña, Graeme Gange, Peter Schachte, Peter J. Stuckey

Modeling discrete optimization problems is not straightforward. It is often the case that precompiling a subproblem that involves only a few tightly constrained variables as a table constraint can improve solving time. Nevertheless, enumerating all the solutions of a subproblem into a table can be costly in time and space. In this work we propose using Multivalued Decision Diagrams (MDDs) and formulas

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-09-11
Xiaojuan Liao, Miyuki Koshimura, Kazuki Nomoto, Suguru Ueda, Yuko Sakurai, Makoto Yokoo

The Coalition Structure Generation (CSG) problem plays an important role in the domain of coalition games. Its goal is to create coalitions of agents so that the global welfare is maximized. To date, Weighted Partial MaxSAT (WPM) encoding has shown high efficiency in solving the CSG problem, which encodes a set of constraints into Boolean propositional logic and employs an off-the-shelf WPM solver

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-11-23
Kostas Stergiou

CP solvers predominantly use arc consistency (AC) as the default propagation method for binary constraints. Many stronger consistencies, such as triangle consistencies (e.g. RPC and maxRPC) exist, but their use is limited despite results showing that they outperform AC on many problems. This is due to the intricacies involved in incorporating them into solvers. On the other hand, singleton consistencies

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-08-25
Michael Codish, Alice Miller, Patrick Prosser, Peter J. Stuckey

Many complex combinatorial problems arising from a range of scientific applications (such as computer networks, mathematical chemistry and bioinformatics) involve searching for an undirected graph satisfying a given property. Since for any possible solution there can be a large number of isomorphic representations, these problems can quickly become intractable. One way to mitigate this problem is to

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-06-16
Vinasetan Ratheil Houndji

Constraint Programming (CP) is a paradigm derived from artificial intelligence, operational research, and algorithmics that can be used to solve combinatorial problems. CP solves problems by interleaving search (assign a value to an unassigned variable) and propagation. Constraint propagation aims at removing/filtering inconsistent values from the domains of the variables in order to reduce the search

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-06-30
Achref El Mouelhi

The study of broken-triangles is becoming increasingly ambitious, by both solving constraint satisfaction problems (CSPs) in polynomial time and reducing search space size through either value merging or variable elimination. Considerable progress has been made in extending this important concept, such as dual broken-triangle and weakly broken-triangle, in order to maximize the number of captured tractable

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-07-12
Julien Vion, Sylvain Piechowiak

In this paper, we present a new conversion of multivalued decision diagrams (MDD) to binary decision diagrams (BDD) which can be used to improve MDD-based fil- tering algorithms such as MDDC or MDD-4R. We also propose BDDF, an algorithm that copies modified parts of the BDD “on the fly” during the search of a solution, and yields a better incrementality than a pure MDDC-like approach. MDDC is not very

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-07-02
Enrico Giunchiglia, Marco Maratea, Luca Pulina

Disjunctive Temporal Problems (DTPs) with Preferences (DTPPs) extend DTPs with piece-wise constant preference functions associated to each constraint of the form l ≤ x − y ≤ u, where x,y are (real or integer) variables, and l,u are numeric constants. The goal is to find an assignment to the variables of the problem that maximizes the sum of the preference values of satisfied DTP constraints, where

更新日期：2020-04-18
• Constraints (IF 1.106) Pub Date : 2018-07-05
Alexander Schiendorfer, Alexander Knapp, Gerrit Anders, Wolfgang Reif

Over-constrained problems are ubiquitous in real-world decision and optimization problems. Plenty of modeling formalisms for various problem domains involving soft constraints have been proposed, such as weighted, fuzzy, or probabilistic constraints. All of them were shown to be instances of algebraic structures. In terms of modeling languages, however, the field of soft constraints lags behind the

更新日期：2020-04-18
• Constraints Pub Date : 2010-11-06
R Marinescu,R Dechter

AND/OR search spaces accommodate advanced algorithmic schemes for graphical models which can exploit the structure of the model. We extend and evaluate the depth-first and best-first AND/OR search algorithms to solving 0-1 Integer Linear Programs (0-1 ILP) within this framework. We also include a class of dynamic variable ordering heuristics while exploring an AND/OR search tree for 0-1 ILPs. We demonstrate

更新日期：2019-11-01
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