One-dimensional Global Optimization Problems with Multiextremal Constraints

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  • Falah M.H. Khalaf
  • Dmitri E. Kvasov
  • Yaroslav D. Sergeyev

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https://doi.org/10.1685/

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Lipschitz univariate constrained global optimization problems where both the objective function and constraints can be multiextremal and non-differentiable are considered. The constrained problem is reduced to a discontinuous unconstrained problem by the index scheme without introducing additional parameters or variables. A new geometric method using adaptive estimates of Lipschitz constants is described, its convergence conditions are established. Numerical experiments including comparison of the new algorithm with methods using penalty approach are given. Algorithms with local tuning technique on behaviour of both the objective function and constraints are considered. [DOI: 10.1685 / CSC06100] About DOI

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2007-10-01

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##issue.vol## 1 (2006)

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Articles

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