Convexification and Global Optimization in Continuous And
Convexification and Global Optimization in Continuous And
Safe bounds in linear and mixed-integer linear programming
Mathematical Programming: Series A and B
Efficient and Safe Global Constraints for Handling Numerical Constraint Systems
SIAM Journal on Numerical Analysis
Safe and tight linear estimators for global optimization
Mathematical Programming: Series A and B
Using constraint techniques for a safe and fast implementation of optimality-based reduction
Proceedings of the 2007 ACM symposium on Applied computing
ICOS: a branch and bound based solver for rigorous global optimization
Optimization Methods & Software - GLOBAL OPTIMIZATION
Journal of Global Optimization
Finding the maximal pose error in robotic mechanical systems using constraint programming
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
ICN-RE: redundancy elimination for information-centric networking
Proceedings of the second edition of the ICN workshop on Information-centric networking
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Interval methods have shown their ability to locate and prove the existence of a global optima in a safe and rigorous way. Unfortunately, these methods are rather slow. Efficient solvers for optimization problems are based on linear relaxations. However, the latter are unsafe, and thus may overestimate, or, worst, underestimate the very global minima. This paper introduces QuadOpt, an efficient and safe framework to rigorously bound the global optima as well as its location. QuadOpt uses consistency techniques to speed up the initial convergence of the interval narrowing algorithms. A lower bound is computed on a linear relaxation of the constraint system and the objective function. All these computations are based on a safe and rigorous implementation of linear programming techniques. First experimental results are very promising.