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Nonconvex Optimization and Its Applications Volume 33 Managing Editors: Panos Pardalos University of Florida, U.S.A. Reiner Horst University ofTrier, Germany Advisory Board: Ding-Zhu Du University of Minnesota, U.S.A. C. A. Floudas Princeton University, U.SA.

J. Mockus Stanford University, U.S.A. H. D. Sherali Virginia Polytechnic Institute and State University, U.S.A.

The titfes pubfished in this se ries are Iisted at the end of this vofwlle.

Handbook of Test Problems in Local and Global Optimization by

Christodoulos A. Floudas Department of Chemical Engineering, Princeton University, Princeton, N.}., U.S.A.

Panos M. Pardalos Department of Industrial and Systems Engineering, University of Florida and

Claire S. Adjiman William R. Esposito Zeynep H. Gümü~ Stephen T. Harding John L. Klepeis Clifford A. Meyer Carl A. Schweiger Department of Chemical Engineering, Princeton University. Princeton, N.}., U.S.A.

Springer-Science+Business Media, B.V.

A C.I.P. Catalogue record for this book is available from the Library of Congress.

ISBN 978-1-4419-4812-0 ISBN 978-1-4757-3040-1 (eBook) DOI 10.1007/978-1-4757-3040-1

Printed on acid-free paper

All Rights Reserved © 1999 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 1999. Softcover reprint ofthe hardcover 1st edition 1999 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. inc1uding photocopying. recording or by any information storage and retrieval system. without written permission from the copyright owner

Preface Significant research activities have taken place in the areas of local and global optimization in the last two decades. Many new theoretical, computational, algorithmic, and software contributions have resulted. It has been realized that despite these numerous contributions, there does not exist a systematic forum for thorough experimental computational testing and· evaluation of the proposed optimization algorithms and their implementations. Well-designed nonconvex optimization test problems are of major importance for academic and industrial researchers interested in algorithmic and software development. It is remarkable that eventhough nonconvex models dominate all the important application areas in engineering and applied sciences, there is only a limited dass of reported representative test problems. This book reflects our long term efforts in designing a benchmark database and it is motivated primarily from the need for nonconvex optimization test problems. The present collection of benchmarks indudes test problems from literature studies and a large dass of applications that arise in several branches of engineering and applied science. C.A. Floudas P.M. Pardalos C.S. Adjiman W.R. Esposito Z.H. Gümü§ S.T. Harding J.L. Klepeis C.A. Meyer C.A. Schweiger

Princeton, New Jersey February 1999

v

Contents 1

1 Introduction 2 Quadratic Programming Problems 2.1 Introduction .. 2.2 Test Problem 1 2.3 Test Proble