Modeling and Optimization: Theory and Applications: Selected Contributions from the MOPTA 2012 Conference (Springer Proceedings in Mathematics & Statistics Book 62)

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 July 30-August 1, 2012. 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 optimization techniques in finance, logistics, 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-- Source other than the Library of Congress Recent Progress in Modeling Unit Commitment Problems -- Miguel F. Anjos Portfolio Optimization with Combinatorial and Downside Return Constraints -- Miguel A. Lejeune -- An Initialization Strategy for High-Dimensional Surrogate-Based Expensive Black-Box Optimization / -- Rommel G. Regis Smoothing and Regularization for Mixed-Integer Second-Order Cone Programming with Applications in Portfolio Optimization -- Hande Y. Benson, Ümit Saǧlam e Duality Between the Perceptron Algorithm and the von Neumann Algorithm -- Dan Li, Tamás Terlaky. Front Matter....Pages i-vii Recent Progress in Modeling Unit Commitment Problems....Pages 1-29 Portfolio Optimization with Combinatorial and Downside Return Constraints....Pages 31-50 An Initialization Strategy for High-Dimensional Surrogate-Based Expensive Black-Box Optimization....Pages 51-85 Smoothing and Regularization for Mixed-Integer Second-Order Cone Programming with Applications in Portfolio Optimization....Pages 87-111 The Duality Between the Perceptron Algorithm and the von Neumann Algorithm....Pages 113-136