Modeling and Optimization: Theory and Applications: MOPTA, Bethlehem, PA, USA, August 2016 Selected Contributions

by Martin Takác, Tamás Terlaky

Overview

This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 17-19, 2016. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and shastic optimization techniques in energy, finance, logistics, analytics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.

Product Details

ISBN-13:	9783319666150
Publisher:	Springer International Publishing
Publication date:	11/29/2017
Series:	Springer Proceedings in Mathematics & Statistics , #213
Edition description:	1st ed. 2017
Pages:	162
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Shastic Decision Problems with Multiple Risk-averse Agents (Getachew K. Befekadu, Alexander Veremyev, Vladimir Boginski, Eduardo L. Pasiliao).- Optimal Packing of General Ellipses in a Circle (Frank J. Kampas, János D. Pintér, Ignacio Castillo).- Column Generation Approach to the Convex Recoloring Problem on a Tree (Sunil Chopra, Ergin Erdem, Eunseok Kim, Sangho Shim).- A Variational Inequality Formulation of a Migration Model with Random Data (Baasansuren Jadamba, Fabio Raciti).- Identification in Mixed Variational Problems by Adjoint Methods with Applications (M. Cho, B. Jadamba, A. A. Khan, A. A. Oberai, M. Sama).- Minimization of the L_p-norm, p ≥ 1 of Dirichlet-type Boundary Controls for the 1D Wave Equation (Ilya Smirnov, Anastasia Dmitrieva).- Projected Semi-Shastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption (JieLiu and Martin Takáč).- Exact Separation of k-Projection Polytope Constraints (Elspeth Adams, Miguel F. Anjos).- Univariate Polynomial Optimization with Sum-of-Squares Interpolants (Dávid Papp).