Titlebook: Integration of AI and OR Techniques in Constraint Programming; 14th International C Domenico Salvagnin,Michele Lombardi Conference proceedi

avenge

In Search of Balance: The Challenge of Generating Balanced Latin Rectanglesnt a challenging problem and there is a need for efficient methods to generate them. Motivated by a real-world application, we consider a natural extension to this problem, balanced Latin Rectangles. Balanced Latin Rectangles appear to be even more defiant than balanced Latin Squares, to such an ext

EVICT

Debugging Unsatisfiable Constraint Models Existing algorithms for computing Minimal Unsatisfiable Subsets (MUSes) can help explain to a user which sets of constraints are causing unsatisfiability. However, these algorithms are usually not aimed at high-level, structured constraint models, and tend to not scale well for them. Furthermore, w

懒惰人民

Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimizationd (DTIP) can be used to learn good trees up to depth 5 from data sets of size up to 1000. In addition to being efficient, our new formulation allows for a lot of flexibility. Experiments show that we can use the trees learned from any existing decision tree algorithms as starting solutions and impro

马笼头

大包裹

aquatic

A Hybrid Approach for Stator Winding Design Optimizationstallation. Engineering these one-of-a-kind designs requires a considerable amount of time and effort, with no guarantees that the final blueprint is cost-optimal. One part of the design involves the stator windings, i.e. the static part of an electric motor generating an electromagnetical field. In

Gesture

myriad

Explanation-Based Weighted Degreerved that when using large arity constraints, its efficiency deteriorates significantly since it loses its ability to discriminate variables. A possible answer to this drawback is to weight a conflict set rather than the entire scope of a failed constraint..We implemented this method for three commo

Indurate

Counting Weighted Spanning Trees to Solve Constrained Minimum Spanning Tree Problems a generalization of the former result to compute in pseudo-polynomial time the exact number of spanning trees of any given weight, and in particular the number of minimum spanning trees. We derive two ways to compute solution densities, one of them exhibiting a polynomial time complexity. These sol

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