Generalized Proximal Point Algorithms for Quasiconvex Programming
نویسندگان
چکیده
In this paper, we proposed algorithms interior proximal methods based on entropylike distance for the minimization of the quasiconvex function subjected to nonnegativity constraints. Under the assumptions that the objective function is bounded below and continuously differentiable, we established the well definedness of the sequence generated by the algorithms and obtained two important convergence results, the principal one is a sufficient condition for the convergence point of the sequence generated by the algorithms is a point of solution of the problem.
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