A new projective exact penalty function for a general constrained optimization

نویسندگان

چکیده

A new projective exact penalty function method is proposed for the equivalent reduction of constrained optimization problems to unconstrained ones. In method, original objective extended infeasible points by summing its value at projection an point on feasible set with distance set. The equivalence means that local and global minimums coincide. Nonconvex sets multivalued projections are admitted, may be lower semicontinuous. particular case convex included. So does not assume existence outside allowable area require selection coefficient.

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ژورنال

عنوان ژورنال: Reports of the National Academy of Sciences of Ukraine

سال: 2022

ISSN: ['2518-153X', '1025-6415']

DOI: https://doi.org/10.15407/dopovidi2022.04.023