{ "id": "1307.4302", "version": "v1", "published": "2013-07-15T13:59:30.000Z", "updated": "2013-07-15T13:59:30.000Z", "title": "Lipschitz gradients for global optimization in a one-point-based partitioning scheme", "authors": [ "Dmitri E. Kvasov", "Yaroslav D. Sergeyev" ], "comment": "25 pages, 4 figures, 5 tables. arXiv admin note: text overlap with arXiv:1103.2056", "journal": "Journal of Computational and Applied Mathematics Volume 236, Issue 16, October 2012, Pages 4042-4054", "doi": "10.1016/j.cam.2012.02.020", "categories": [ "math.OC", "cs.MS", "cs.NA", "math.NA" ], "abstract": "A global optimization problem is studied where the objective function $f(x)$ is a multidimensional black-box function and its gradient $f'(x)$ satisfies the Lipschitz condition over a hyperinterval with an unknown Lipschitz constant $K$. Different methods for solving this problem by using an a priori given estimate of $K$, its adaptive estimates, and adaptive estimates of local Lipschitz constants are known in the literature. Recently, the authors have proposed a one-dimensional algorithm working with multiple estimates of the Lipschitz constant for $f'(x)$ (the existence of such an algorithm was a challenge for 15 years). In this paper, a new multidimensional geometric method evolving the ideas of this one-dimensional scheme and using an efficient one-point-based partitioning strategy is proposed. Numerical experiments executed on 800 multidimensional test functions demonstrate quite a promising performance in comparison with popular DIRECT-based methods.", "revisions": [ { "version": "v1", "updated": "2013-07-15T13:59:30.000Z" } ], "analyses": { "subjects": [ "65K05", "90C26", "90C56" ], "keywords": [ "global optimization", "one-point-based partitioning scheme", "lipschitz gradients", "multidimensional test functions demonstrate quite", "multidimensional black-box function" ], "tags": [ "journal article" ], "note": { "typesetting": "TeX", "pages": 25, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2013arXiv1307.4302K" } } }