Dynamic and Hierarchical Constraints Solver with Continuous Variables

Research in the area of layout, graphics, computer-aided design (CAD), and visualization includes novel t echniques of artificial i ntelligence discipline, to express problems in terms of numeric c onstraint satisfaction p roblem over continuous domains. However, in those applications, a constraints solver must support both functional and non- functional constraints, and must fi nd a solution even in critical situations s uch a s over- constraint problem. Furthermore, it must incrementally update the solutions spaces as new constraints are added, existing constraints are removed, and constraints s trength a re changed. In this paper, in order to surmount those difficulties, we present a new constraints solver called ORANOS. ORANOS is an incremental constraints solver, independent from domain, by using interval propagation technique to efficiently maintain both equality and inequality constraints organized in a constraints hierarchy.