the fixed-template constraint satisfaction problem (CSP) can be seen as the problem of deciding whether a given primitive positive first-order sentence is true in a fixed structure (also called model). We study a clas...
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We introduce the Confidence constraint, a chance constraintthat ensures, with probability, that a set of variables are no smaller than random variables for which the probability distribution is given. this constraint...
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the argmax function returns the index of the (first copy of the) maximum value occuring in a list of values. argmax is important in models where we choose a characteristic value based on a seperate criteria, and for m...
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Domain reduction is an essential tool for solving the constraint satisfaction problem (CSP). In the binary CSP, neighbourhood substitution consists in eliminating a value if there exists another value which can be sub...
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the problem of transporting vehicle components in a car manufacturer workshop can be seen as a large scale single vehicle pickup and delivery problem with periodic time windows. Our experimental evaluation indicates t...
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Dashed strings are a formalism for modelling the domain of string variables when solving combinatorial problems with string constraints. In this work we focus on (variants of) the Replace constraint, which aims to fin...
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constraintprogramming models have been recently proposed to solve cryptanalysis problems for symmetric block ciphers such as AES. these models are more efficient than dedicated approaches but their design is difficul...
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principles and practice of constraintprogramming--cp98 : 4thinternationalconference, cp98, Pisa, Italy, October 26-30, 1998 : Proceedings by cp98 (1998 : Pisa, Italy); Maher, Michael, 1959-; Puget, Jean-Francois; p...
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principles and practice of constraintprogramming--cp98 : 4thinternationalconference, cp98, Pisa, Italy, October 26-30, 1998 : Proceedings by cp98 (1998 : Pisa, Italy); Maher, Michael, 1959-; Puget, Jean-Francois; published by Berlin ; New York : Springer
the Virtual Arc Consistency (VAC) algorithm by Cooper et al. is a soft local consistency technique that computes, in linear space, a bound on the basic LP relaxation of the Weighted CSP (WCSP). We generalize this tech...
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Block-coordinate descent (BCD) is a popular method in large-scale optimization. Unfortunately, its fixed points are not global optima even for convex problems. A succinct characterization of convex problems optimally ...
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