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A Nonmonotone Adaptive-BFGS Trust-Region Method

Shujie Jing, Xiaoliang Zhang

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Abstract

A nonmonotone adaptive-BFGS trust-region method for unconstrained optimization is presented.Not only the trust-region radius in this method is automatically determined by using first order information,but combining with the advantage of the BFGS algorithm.Under certain conditions,the global and superlinear convergences of the algorithm are proved.

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A nonmonotone adaptive-BFGS trust-region method for unconstrained optimization is presented.Not only the trust-region radius in this method is automatically determined by using first order information,but combining with the advantage of the BFGS algorithm.Under certain conditions,the global and superlinear convergences of the algorithm are proved.

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Available abstract

A nonmonotone adaptive-BFGS trust-region method for unconstrained optimization is presented.Not only the trust-region radius in this method is automatically determined by using first order information,but combining with the advantage of the BFGS algorithm.Under certain conditions,the global and superlinear convergences of the algorithm are proved.

Key concepts: Broyden–Fletcher–Goldfarb–Shanno algorithm, Trust region, Computer science, Mathematical optimization, RADIUS, Order (exchange), Algorithm, Mathematics

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