Approximation and Optimization

Edited by Ioannis C. Demetriou () and Panos M. Pardalos ()

in Springer Optimization and Its Applications from Springer, currently edited by Pardalos, Panos, Thai, My T. and Du, Ding-Zhu

Date: 2019
ISBN: 978-3-030-12767-1
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Chapters in this book:

Introduction

Ioannis C. Demetriou and Panos M. Pardalos

Evaluation Complexity Bounds for Smooth Constrained Nonlinear Optimization Using Scaled KKT Conditions and High-Order Models

Coralia Cartis, Nicholas I. M. Gould and Philippe L. Toint

Data-Dependent Approximation in Social Computing

Weili Wu, Yi Li, Panos M. Pardalos and Ding-Zhu Du

Multi-Objective Evolutionary Optimization Algorithms for Machine Learning: A Recent Survey

Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis and Michael N. Vrahatis

No Free Lunch Theorem: A Review

Stavros P. Adam, Stamatios-Aggelos N. Alexandropoulos, Panos M. Pardalos and Michael N. Vrahatis

Piecewise Convex–Concave Approximation in the Minimax Norm

Michael P. Cullinan

A Decomposition Theorem for the Least Squares Piecewise Monotonic Data Approximation Problem

Ioannis C. Demetriou

Recent Progress in Optimization of Multiband Electrical Filters

Andrei Bogatyrëv

Impact of Error in Parameter Estimations on Large Scale Portfolio Optimization

Valery A. Kalyagin and Sergey V. Slashchinin

Optimal Design of Smart Composites

Georgios K. Tairidis, Georgia Foutsitzi and Georgios E. Stavroulakis

Tax Evasion as an Optimal Solution to a Partially Observable Markov Decision Process

Paraskevi Papadopoulou and Dimitrios Hristu-Varsakelis

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DOI: 10.1007/978-3-030-12767-1

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