Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem. We aim at determining the time complexity of arc consistency testing. The input structures G and H can be supposed to be connected colored graphs, as the general problem reduces to this particular case. We first observe the upper bound O(e(G)v(H) + v(G)e(H)), ...

MINTO is a software system that solves mixed integer linear programs by a branch and bound algorithm with linear programming relaxations It also provides automatic constraint classi cation preprocessing primal heuristics and constraint generation Moreover the user can enrich the basic algorithm by providing a variety of specialized application routines that can customize MINTO to achieve maximu...

We address task scheduling on multiprocessor computers with dynamically variable voltage and speed as a combinatorial optimization problem. We define the problem of minimizing schedule length with energy consumption constraint on multiprocessor computers. We derive a lower bound for the optimal schedule length for the problem of minimizing schedule length with energy consumption constraint.

We present a new approach to enhancing Answer Set Programming (ASP) with Constraint Processing techniques which allows for solving interesting Constraint Satisfaction Problems in ASP. We show how constraints on finite domains can be decomposed into logic programs such that unit-propagation achieves arc, bound or range consistency. Experiments with our encodings demonstrate their computational i...

This 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 sim...

I analyze informative equilibria between two senders and one receiver who share compatible interests. The receiver’s action is restricted since an action is costly. If the action is severely bound only in one dimension, information can be fully transmitted irrespective of the constraint degree. When the action is bound in both dimensions, full information revelation is still possible as long as...

The Same constraint takes two sets of variables X and Z such that jX j= jZj and assigns values to them such that the multiset of values assigned to the variables in X is equal to the multiset of values assigned to the variables in Z. In this paper we extend the Same constraint in a GCC-like manner by adding cardinality requirements on the values. That is, for each value we have a lower and uppe...

This paper introduces a global constraint encapsulating a regular constraint together with several cumulative costs. It is motivated in the context of personnel scheduling problems, where a schedule meets patterns and occurrence requirements which are intricately bound. The optimization problem underlying the multicost-regular constraint is NP-hard but it admits an efficient Lagrangian relaxati...

Constraint toolkits generally propose a sum constraint where a global objective variable should be equal to a sum of local objective variables, on which bound-consistency is achieved. To solve optimization problems this propagation is poor. Therefore, ad-hoc techniques are designed for pruning the global objective variable by taking account of the interactions between constraints defined on loc...

The multiple knapsack problem (MKP) is a classical combinatorial optimization problem. A recent algorithm for some classes of the MKP is bin-completion, a bin-oriented, branch-and-bound algorithm. In this paper, we propose path-symmetry and path-dominance, which are instances of the symmetry detection by dominance detection approach for pruning symmetric nodes in the MKP branch-and-bound search...