Enriching Solutions to Combinatorial Problems via Solution Engineering

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

Un solveur de contraintes basé sur les domaines abstraits

International audienceDans cet article, nous utilisons des techniques de l'interpréation abstraite (une théorie d'approximation des sémantiques) dans le cadre de la programmation par contraintes (basée sur la logique du premier ordre qui permet de résoudre des problèmes combinatoires). Nous mettons en évidence certains liens et différences entre ces domaines de recherches : tous deux calculent itérativement des points fixes mais emploient des extrapolations et stratégies de raffinement différentes. De plus, nous pouvons mettre en correspondance les consistances en programmation par contraintes et les domaines abstraits non relationnels. Nous utilisons ensuite ces correspondances pour construire un solveur de contraintes abstrait qui s'appuie sur des techniques d'interprétation abstraite (comme les domaines relationnels) pour aller au-delà des solveurs classiques. Les résultats expérimentaux obtenus avec notre prototype sont encourageants

A Constraint Solver based on Abstract Domains

International audienceIn this article, we apply techniques from Abstract Interpretation (a general theory of semantic abstractions) to Constraint Programming (which aims at solving hard combinatorial problems with a generic framework based on first-order logics). We highlight some links and differences between these fields: both compute fixpoints by iteration but employ different extrapolation and refinement strategies; moreover, consistencies in Constraint Programming can be mapped to non-relational abstract domains. We then use these correspondences to build an abstract constraint solver that leverages abstract interpretation techniques (such as relational domains) to go beyond classic solvers. We present encouraging experimental results obtained with our prototype implementation

A Constraint on the Number of Distinct Vectors with Application to Localization

International audienceThis paper introduces a generalization of the "nvalue" constraint that bounds the number of distinct values taken by a set of variables.The generalized constraint (called "nvector") bounds the number of distinct (multi-dimensional) vectors. The first contribution of this paper is to show that this global constraint has a significant role to play with continuous domains, by taking the example of simultaneous localization and map building (SLAM). This type of problem arises in the context of mobile robotics. The second contribution is to prove that enforcing bound consistency on this constraint is NP-complete. A simple contractor (or propagator) is proposed and applied on a real application

Global Constraint Catalog, 2nd Edition

This report presents a catalogue of global constraints where each constraint is explicitly described in terms of graph properties and/or automata and/or first order logical formulae with arithmetic. When available, it also presents some typical usage as well as some pointers to existing filtering algorithms

Global Constraint Catalog, 2nd Edition (revision a)

This report presents a catalogue of global constraints where each constraint is explicitly described in terms of graph properties and/or automata and/or first order logical formulae with arithmetic. When available, it also presents some typical usage as well as some pointers to existing filtering algorithms