Global optimization of non-convex piecewise linear regression splines
نویسندگان
چکیده
منابع مشابه
network optimization with piecewise linear convex costs
the problem of finding the minimum cost multi-commodity flow in an undirected and completenetwork is studied when the link costs are piecewise linear and convex. the arc-path model and overflowmodel are presented to formulate the problem. the results suggest that the new overflow model outperformsthe classical arc-path model for this problem. the classical revised simplex, frank and wolf and a ...
متن کاملNetwork Optimization with Piecewise Linear Convex Costs
The problem of finding the minimum cost multi-commodity flow in an undirected and complete network is studied when the link costs are piecewise linear and convex. The arc-path model and overflow model are presented to formulate the problem. The results suggest that the new overflow model outperforms the classical arc-path model for this problem. The classical revised simplex, Frank and Wolf and...
متن کاملConvex piecewise-linear fitting
We consider the problem of fitting a convex piecewise-linear function, with some specified form, to given multi-dimensional data. Except for a few special cases, this problem is hard to solve exactly, so we focus on heuristic methods that find locally optimal fits. The method we describe, which is a variation on the K-means algorithm for clustering, seems to work well in practice, at least on d...
متن کاملUnified Methods for Exploiting Piecewise Linear Structure in Convex Optimization
We develop methods for rapidly identifying important components of a convex optimization problem for the purpose of achieving fast convergence times. By considering a novel problem formulation—the minimization of a sum of piecewise functions—we describe a principled and general mechanism for exploiting piecewise linear structure in convex optimization. This result leads to a theoretically justi...
متن کاملExplicit Univariate Global Optimization with Piecewise Linear Support Functions
Piecewise linear convex and concave support functions combined with Pijavskii’s method are proposed to be used for solving global optimization problems. Rules for constructing support functions are introduced.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Global Optimization
سال: 2017
ISSN: 0925-5001,1573-2916
DOI: 10.1007/s10898-016-0494-5