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52
Constraint Programming
, 2006
"... Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, operations research, algorithms, graph theory and elsewhere. The basic idea in constraint programming is that the user states the constraints ..."
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Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, operations research, algorithms, graph theory and elsewhere. The basic idea in constraint programming is that the user states the constraints and a general purpose constraint solver is used to solve them.
Solving a Telecommunications Feature Subscription Configuration Problem
 In CP
, 2008
"... Abstract. Call control features (e.g., calldivert, voicemail) are primitive options to which users can subscribe offline to personalise their service. The configuration of a feature subscription involves choosing and sequencing features from a catalogue and is subject to constraints that prevent ..."
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Abstract. Call control features (e.g., calldivert, voicemail) are primitive options to which users can subscribe offline to personalise their service. The configuration of a feature subscription involves choosing and sequencing features from a catalogue and is subject to constraints that prevent undesirable feature interactions at runtime. When the subscription requested by a user is inconsistent, one problem is to find an optimal relaxation. In this paper, we show that this problem is NPhard and we present a constraint programming formulation using the variable weighted constraint satisfaction problem framework. We also present simple formulations using partial weighted maximum satisfiability and integer linear programming. We experimentally compare our formulations of the different approaches; the results suggest that our constraint programming approach is the best of the three overall. 1
Constrained Metabolic Network Analysis: Discovering Pathways Using CP(Graph)
, 2005
"... this paper. It also shows that a graph variable has an inherent constraints linking its arcs to its nodes ..."
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this paper. It also shows that a graph variable has an inherent constraints linking its arcs to its nodes
A Connectivity Constraint using Bridges
 In ECAI
, 2006
"... We present a specialised constraint for enforcing graph connectivity. It is assumed that we have a square symmetrical array A of 0/1 constrained integer variables representing potential undirected edges in a simple graph, such that variable A[u, v] corresponds to ..."
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We present a specialised constraint for enforcing graph connectivity. It is assumed that we have a square symmetrical array A of 0/1 constrained integer variables representing potential undirected edges in a simple graph, such that variable A[u, v] corresponds to
LS(Graph & Tree): A Local Search Framework for Constraint Optimization on Graphs and Trees Pham Quang
"... LS(Graph & Tree) is a local search framework which aims at simplifying the modeling of Constraint Satisfaction Optimization Problems on graphs (CSOP on graphs or GCSOP). Optimum Constrained Trees (OCT) problems (a subclass of CSOP on graphs) in which we need to find an optimum subtree with addit ..."
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LS(Graph & Tree) is a local search framework which aims at simplifying the modeling of Constraint Satisfaction Optimization Problems on graphs (CSOP on graphs or GCSOP). Optimum Constrained Trees (OCT) problems (a subclass of CSOP on graphs) in which we need to find an optimum subtree with additional constraints of a given weighted graph arise in many reallife applications. This paper introduces the LS(Graph & Tree) framework and local search abstractions for OCT problems. These abstractions are applied to model and solve the edge weighted kCardinality Tree (KCT) problem. The modeling as well as experimental results show the significance of the abstractions.
Comparing ASP and CP on Four Grid Puzzles
"... We study two declarative programming languages namely Answer Set Programming (ASP) and Constraint Programming (CP) on four grid puzzles: Akari, Kakuro, Nurikabe, and Heyawake. We represent these problems in both formalisms in a systematic way and compute their solutions using ASP system Clasp and CP ..."
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We study two declarative programming languages namely Answer Set Programming (ASP) and Constraint Programming (CP) on four grid puzzles: Akari, Kakuro, Nurikabe, and Heyawake. We represent these problems in both formalisms in a systematic way and compute their solutions using ASP system Clasp and CP system Comet. We compare the ASP approach with the CP approach both from the point of view of knowledge representation and from the point of view of computational time and memory. 1
Atom Mapping with Constraint Programming
"... The mass flow in a chemical reaction network is determined by the propagation of atoms from educt to product molecules within each of the constituent chemical reactions. The Atom Mapping Problem for a given chemical reaction is the computational task of determining the correspondences of the atoms ..."
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The mass flow in a chemical reaction network is determined by the propagation of atoms from educt to product molecules within each of the constituent chemical reactions. The Atom Mapping Problem for a given chemical reaction is the computational task of determining the correspondences of the atoms between educt and product molecules. We propose here a Constraint Programming approach to identify atom mappings for “elementary ” reactions. These feature a cyclic imaginary transition state (ITS) imposing an additional strong constraint on the bijection between educt and product atoms. The ongoing work presented here identifies only chemically feasible ITSs by integrating the cyclic structure of the chemical transformation into the search.
Improving the asymmetric TSP by considering graph structure. arXiv preprint arXiv:1206.3437
, 2012
"... Abstract. Recent works on cost based relaxations have improved Constraint Programming (CP) models for the Traveling Salesman Problem (TSP). We provide a short survey over solving asymmetric TSP with CP. Then, we suggest new implied propagators based on general graph properties. We experimentally sho ..."
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Abstract. Recent works on cost based relaxations have improved Constraint Programming (CP) models for the Traveling Salesman Problem (TSP). We provide a short survey over solving asymmetric TSP with CP. Then, we suggest new implied propagators based on general graph properties. We experimentally show that such implied propagators bring robustness to pathological instances and highlight the fact that graph structure can significantly improve search heuristics behavior. Finally, we show that our approach outperforms current state of the art results. 1
Graph properties based filtering
, 2006
"... Abstract. This article presents a generic filtering scheme, based on the graph description of global constraints. This description is defined by a network of binary constraints and a list of elementary graph properties: each solution of the global constraint corresponds to a subgraph of the initial ..."
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Abstract. This article presents a generic filtering scheme, based on the graph description of global constraints. This description is defined by a network of binary constraints and a list of elementary graph properties: each solution of the global constraint corresponds to a subgraph of the initial network, retaining only the satisfied binary constraints, and which fulfills all the graph properties. The graphbased filtering identifies the arcs of the network that belong or not to the solution subgraphs. The objective is to build, besides a catalog of global constraints, also a list of systematic filtering rules based on a limited set of graph properties. We illustrate this principle on some common graph properties and provide computational experiments of the effective filtering on thegroup constraint. 1