Optimization Theory: Recent Developments from Mátraháza

Author:   F. Giannessi ,  Panos M. Pardalos ,  Tamás Rapcsák
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 2001
Volume:   59
ISBN:  

9781461379836


Pages:   280
Publication Date:   17 September 2011
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Optimization Theory: Recent Developments from Mátraháza


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Overview

This volume contains refereed papers based on the lectures presented at the XIV International Conference on Mathematical Programming held at Matrahaza, Hungary, between 27-31 March 1999. This conference was organized by the Laboratory of Operations Research and Deci­ sion Systems at the Computer and Automation Institute, Hungarian Academy of Sciences. The editors hope this volume will contribute to the theory and applications of mathematical programming. As a tradition of these events, the main purpose of the confer­ ence was to review and discuss recent advances and promising research trends concerning theory, algorithms and applications in different fields of Optimization Theory and related areas such as Convex Analysis, Complementarity Systems and Variational Inequalities. The conference is traditionally held in the Matra Mountains, and housed by the resort house of the Hungarian Academy of Sciences. This was the 14th event of the long lasting series of conferences started in 1973. The organizers wish to express their thanks to the authors for their contributions in this volume, and the anonymous referees for their valu­ able comments. Special thanks are directed to our sponsors, the Hun­ garian Academy of Sciences, the National Committee for Technological Development, the Hungarian National Science Foundation, and last but not least, the Hungarian Operational Research Society. We would like to thank John Martindale from Kluwer Academic Publishers for helping us produce this volume, Eva Nora Nagy for cor­ rections and proof-readings, and Peter Dombi for his excellent work on typesetting and editing the manuscript.

Full Product Details

Author:   F. Giannessi ,  Panos M. Pardalos ,  Tamás Rapcsák
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 2001
Volume:   59
Dimensions:   Width: 16.00cm , Height: 1.50cm , Length: 24.00cm
Weight:   0.473kg
ISBN:  

9781461379836


ISBN 10:   1461379830
Pages:   280
Publication Date:   17 September 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Heuristics for the Process Network Synthesis Problem.- Heuristics for Simplified Process Network Synthesis (PNS) Problems with a Blossom-Type Algorithm for the Edge Covering Problem.- Lower and Upper Bounds on the Probability of the Union of Some Events with Applications.- The Linear Complementarity Problem and the Class of Generalized Positive Subdefinite Matrices.- Computer Experiences with Successive Regression Approximations for Solving Equations.- A Bundle of Smooth Lagrangians in Mathematical Programming.- A Nontopological Two-function Minimax Theorem with Monotone Ttansformations of the Functional Values.- Non-smooth Optimization with Randomization.- The Sherman-Morrison Formula for the Determinant and its Application for Optimizing Quadratic Functions on Condition Sets Given by Extreme Generators.- Duality For D.C. Optimization Over Compact Sets.- Characterization of Monotone Operators by Using a Special Class of Preinvex Functions.- Two Approaches for Parallelizing the UEGO Algorithm.- Convexification of Functions by Nonlinear Coordinate Transformations.- Packing Equal Circles in a Square I. — Problem Setting and Bounds for Optimal Solutions.- Packing Equal Circles in a Square II. — New Results for up to 100 Circles Using the TAMSASS-PECS Algorithm.- On Duality for Quasi-convex Supremization and Reverse Convex Infimization.- A Minimization Problem in Function Spaces.

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