Communication Dans Un Congrès Année : 2019

Reliable Bounds for Convex Relaxation in Interval Global Optimization Codes

Résumé

In order to obtain reliable deterministic global optima, all the computed bounds have to be certified in a way that no numerical error due to floating-point operations can discard a feasible solution. Interval arithmetic Branch and Bound algorithms which are developed since the 1980th possess this property of reliability. However, some new accelerating techniques, such as convex relaxation, could improve the convergence of those reliable global optimization algorithms while keeping the property of reliability. In this work, we show that a floating-point solution obtained by solving a relaxed convex program can be corrected in order to certify that this new lower bound is lower than the real global optimum.

Dates et versions

hal-03942322 , version 1 (17-01-2023)

Identifiants

Citer

Frédéric Messine, Gilles Trombettoni. Reliable Bounds for Convex Relaxation in Interval Global Optimization Codes. LeGO 2018 - 14th International Global Optimization Workshop, Sep 2018, Leiden, Netherlands. pp.020050, ⟨10.1063/1.5090017⟩. ⟨hal-03942322⟩
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