Constructing large feasible suboptimal intervals for constrained nonlinear optimization | Zendy

Tibor Csendes | Zendy; Zelda B. Zabinsky | Zendy; Birna P. Kristinsdottir | Zendy

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Constructing large feasible suboptimal intervals for constrained nonlinear optimization

Author(s) -

Tibor Csendes,

Zelda B. Zabinsky,

Birna P. Kristinsdottir

Publication year - 1995

Publication title -

annals of operations research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.068

H-Index - 105

eISSN - 1572-9338

pISSN - 0254-5330

DOI - 10.1007/bf02096403

Subject(s) - interval (graph theory) , theory of computation , mathematical optimization , subdivision , feasible region , interval arithmetic , constrained optimization , mathematics , nonlinear programming , nonlinear system , neighbourhood (mathematics) , point (geometry) , set (abstract data type) , constrained optimization problem , algorithm , computer science , optimization problem , physics , quantum mechanics , mathematical analysis , geometry , archaeology , combinatorics , bounded function , history , programming language

An algorithm for finding a large feasiblen-dimensional interval for constrained global optimization is presented. Then-dimensional interval is iteratively enlarged about a seed point while maintaining feasibility. An interval subdivision method may be used to check feasibility of the growing box. The resultant feasible interval is constrained to lie within a given level set, thus ensuring it is close to the optimum. The ability to determine such a feasible interval is useful for exploring the neighbourhood of the optimum, and can be practically used in manufacturing considerations. The numerical properties of the algorithm are tested and demonstrated by an example problem.

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