Extended cutting angle method of global optimization
Data(s) |
01/01/2008
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Resumo |
Methods of Lipschitz optimization allow one to find and confirm the global minimum of multivariate Lipschitz functions using a finite number of function evaluations. This paper extends the Cutting Angle method, in which the optimization problem is solved by building a sequence of piecewise linear underestimates of the objective function. We use a more flexible set of support functions, which yields a better underestimate of a Lipschitz objective function. An efficient algorithm for enumeration of all local minima of the underestimate is presented, along with the results of numerical experiments. One dimensional Pijavski-Shubert method arises as a special case of the proposed approach.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
Yokohama Publishers |
Relação |
http://dro.deakin.edu.au/eserv/DU:30017549/beliakov-extendedcutting-2008.pdf http://www.ybook.co.jp/online/pjoe/vol4/pjov4n1p153.html |
Direitos |
2008, Yokohama Publishers |
Palavras-Chave | #global optimization #Lipschitz optimization #abstract convexity #cutting angle method #Sawtooth underestimate |
Tipo |
Journal Article |