Convexification in Unconstrained Continuous Optimization

Convexification;Unconstrained Optimization;Applied Mathematics & Statistics

Hong, LingzhouRobinson, Daniel P. ;

Johns Hopkins University

关键词: Convexification;    Unconstrained Optimization;    Applied Mathematics & Statistics;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/37231/HONG-THESIS-2014.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

In this Master’s thesis, we study the role of convexification as it is used in un- constrained optimization of smooth functions. Many variants of convexification exist, but a detailed study of their practical performance has not been performed. We complete such a study in this thesis since the performance of an optimization algorithm is greatly affected by the convexification used. We also propose and validate a new convexification procedure by comparing it with commonly used schemes through a series of extensive numerical experiments; the new procedure performs the best. The results we obtained will likely aid in the design of future optimization algorithms.