State of the Art in Global Optimization Computational Methods and Ap
Optimization problems abound in most fields of science, engineering, and tech nology. In many of these problems it is necessary to compute the global optimum (or a good approximation) of a multivariable function. The variables that define the function to
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Nonconvex Optimization and Its Applications Volume 7
Managing Editors: Panos Pardalos University of Florida, U.S.A.
Reiner Horst University of Trier, Germany
Advisory Board: Ding-ZhuDu University of Minnesota, U.S.A.
C. A. Floudas Princeton University, U.S.A.
G. Infanger Stanford University, U.S.A.
J. Mockus Lithuanian Academy of Sciences, Lithuania
H. D. Sherali Virginia Polytechnic Institute and State University, U.S.A.
The titles published in this series are listed at the end of this volume.
State of the Art in Global Optimization Computational Methods and Applications
Edited by
C. A. Floudas Princeton University
and
P. M. Pardalos University of Florida
KLUWER ACADEMIC PUBLISHERS DORDRECHT I BOSTON I LONDON
A C.I.P. Catalogue record for this book is available from the Library of Congress.
ISBN-13: 978-1-4613-3439-2 001: 10.1007/978-1-4613-3437-8
e-ISBN-13: 978-1-4613-3437-8
Published by Kluwer Academic Publishers, P.O. Box 17,3300 AA Dordrecht, The Netherlands. Kluwer Academic Publishers incorporates the publishing programmes of D. Reidel, Martinus Nijhoff, Dr W. Junk and MTP Press. Sold and distributed in the U.S.A. and Canada by Kluwer Academic Publishers, 101 Philip Drive, Norwell, MA 02061, U.S.A. In all other countries, sold and distributed by Kluwer Academic Publishers Group, P.O. Box 322, 3300 AH Dordrecht, The Netherlands.
Printed on acid-free paper
All Rights Reserved
© 1996 Kluwer Academic Publishers
No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.
Contents Preface ...................................................... ix Lagrange Duality in Partly Convex Programming S. Zlobec .................................................... 1 Global Optimization using Hyperbolic Cross Points
E. Novak and K. Ritter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 19 Global Minimization of Separable Concave Functions under Linear Constraints with Totally Unimodular Matrices
R. Horst and N. van Thoai ....................................... 35 On Existence of Robust Minimizers S. Shi, Q. Zheng and D. Zhuang ................................... 47 A Branch and Bound Algorithm for the Quadratic Assignment Problem using a Lower Bound Based on Linear Programming
K.G. Ramakrishnan, M.G.C. Resende and P.M. Pardalos .................. 57 Dynamic Matrix Factorization Methods for using Formulations Derived from Higher Order Lifting Techniques in the Solution of the Quadratic Assignment Problem
B. Ramachandran and I.F. Pekny .................................. 75 Conical Coercivity Conditions and Global Minimization on Cones. An Existence Result G. Isac ..................................................... 93 The use of Ordinary Differential Equations in Quadratic Maximization with Integer Constraints P. Maponi, M. C. Recchioni and F. Zi
