5 research outputs found

    Propagating Regular Counting Constraints

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    Constraints over finite sequences of variables are ubiquitous in sequencing and timetabling. Moreover, the wide variety of such constraints in practical applications led to general modelling techniques and generic propagation algorithms, often based on deterministic finite automata (DFA) and their extensions. We consider counter-DFAs (cDFA), which provide concise models for regular counting constraints, that is constraints over the number of times a regular-language pattern occurs in a sequence. We show how to enforce domain consistency in polynomial time for atmost and atleast regular counting constraints based on the frequent case of a cDFA with only accepting states and a single counter that can be incremented by transitions. We also prove that the satisfaction of exact regular counting constraints is NP-hard and indicate that an incomplete algorithm for exact regular counting constraints is faster and provides more pruning than the existing propagator from [3]. Regular counting constraints are closely related to the CostRegular constraint but contribute both a natural abstraction and some computational advantages.Comment: Includes a SICStus Prolog source file with the propagato

    A Parametric Propagator for Pairs of Sum Constraints with a Discrete Convexity Property

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    International audienceWe introduce a propagator for pairs of Sum constraints, where the expressions in the sums respect a form of convexity. This propagator is parametric and can be instantiated for various concrete pairs, including Deviation, Spread, and the conjunction of Linear ≤ and Among. We show that despite its generality , our propagator is competitive in theory and practice with state-of-the-art propagators

    Enriching Solutions to Combinatorial Problems via Solution Engineering

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    International audienceExisting approaches to identify multiple solutions to combinatorial problems in practice are at best limited in their ability to simultaneously incorporate both diversity among generated solutions, as well as problem-specific desires that may only be discovered or articulated by the user after further analysis of solver output. We propose a general framework for problems of a combinatorial nature that can generate a set of of multiple (near-)optimal, diverse solutions, that are further infused with desirable features. We call our approach solution engineering. A key novelty is that desirable solution properties need not be explicitly modeled in advance. We customize the framework to both the mathematical programming and constraint programming technologies, and subsequently demonstrate its prac-ticality by implementing and then conducting computational experiments on existing test instances from the literature. Our computational results confirm the very real possibility of generating sets of solutions infused with features that might otherwise remain undiscovered

    XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems

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    In this document, we introduce XCSP3-core, a subset of XCSP3 that allows us to represent constraint satisfaction/optimization problems. The interest of XCSP3-core is multiple: (i) focusing on the most popular frameworks (CSP and COP) and constraints, (ii) facilitating the parsing process by means of dedicated XCSP3-core parsers written in Java and C++ (using callback functions), (iii) and defining a core format for comparisons (competitions) of constraint solvers.Comment: arXiv admin note: substantial text overlap with arXiv:1611.0339

    The SeqBin Constraint Revisited

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    We revisit the SEQBIN constraint [1]. This meta-constraint subsumes a number of important global constraints like CHANGE [2], SMOOTH [3] and INCREASINGNVALUE [4]. We show that the previously proposed filtering algorithm for SEQBIN has two drawbacks even under strong restrictions: it does not detect bounds disentailment and it is not idempotent. We identify the cause for these problems, and propose a new propagator that overcomes both issues. Our algorithm is based on a connection to the problem of finding a path of a given cost in a restricted n-partite graph. Our propagator enforces domain consistency in O(nd 2) and, for special cases of SEQBIN that include CHANGE,SMOOTH and INCREASINGNVALUE in O(nd) time
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