Titlebook: Introduction to Nonsmooth Optimization; Theory, Practice and Adil Bagirov,Napsu Karmitsa,Marko M. M?kel? Book 2014 Springer International P

礦石

SemiAcademic Problemsmum eigenvalue problem that is an important part of many engineering design problems and graph theoretical applications. The interested reader may find more details of each problem class in the Notes and References at the end of Part II.

insecticide

IRS

Book 2014 plays a critical role in many industrial applications and real-world modeling systems, for example in the context of image denoising, optimal control, neural network training, data mining, economics and computational chemistry and physics. The book covers both the theory and the numerical methods u

協(xié)迫

Convex Analysisnot necessarily differentiable functions. We define subgradients and subdifferentials and present some basic results. At the end of this chapter, we link these analytical and geometrical concepts together.

過(guò)多

Optimality Conditionslocally Lipschitz continuous functions by using subgradient information, and present their basic properties. These linearizations are suitable for function approximation. Finally, we define the notion of a descent direction and show how to find it for a locally Lipschitz continuous function.

分開(kāi)如此和諧

Approximations of Subdifferentialsa given point. Finally, we introduce the notion of piecewise partially separable functions and study their properties. In particular, we describe how to calculate the discrete gradient for a piecewise partially separable function.

CLIFF

Subgradient Methodssed NSO methods, although they may suffer from some serious drawbacks (this is true especially with the simplest versions of subgradient methods). The first method to be considered in this chapter is the cornerstone of NSO, the .. Then the ideas of the more sophisticated subgradient method, the well-known . are introduced.

農(nóng)學(xué)

Cutting Plane Methodsion. In this way, more information about the local behavior of the function is obtained than what an individual arbitrary subgradient can yield. In this chapter, we first introduce the basic ideas of the . and then the more advanced ..

Medley

Bundle Methods than what an individual arbitrary subgradient can yield. In this chapter, we first introduce the most frequently used bundle methods, that is, the . and the ., and then we describe the basic ideas of the second order ..

離開(kāi)

Book 2014e theory of NSO;.2. test problems and practical applications;.3. a guide to NSO software..The book is ideal for anyone teaching or attending NSO courses. As an accessible introduction to the ?eld, it is also well suited as an independent learning guide for practitioners already familiar with the basics of optimization.