Stochastic Optimization: Algorithms and Applications
Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunicati
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Applied Optimization Volume 54 Series Editors: Panos M. Pardalos University of Florida, U.S.A. Donald Hearn University of Florida, U.S.A.
Stochastic Optimization: Algorithms and Applications Edited by
Stanislav Uryasev and Panos M. Pardalos Center for Applied Optimization. Department of Industrial and Systems Engineering. University of Florida. 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 978-1-4419-4855-7 ISBN 978-1-4757-6594-6 (eBook) DOI 10.1007/978-1-4757-6594-6
Printed on acidjree paper
All Rights Reserved © 2001 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 2001 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
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Contents Preface ......................................................... xi Output analysis for approximated stochastic programs ..... 1 J. Dupacova 1. Introduction ................................................... 2 2. Methods of output analysis ..................................... 4 3. Concluding remarks ........................................... 22 References ........................................................ 23
Combinatorial Randomized Rounding: Boosting Randomized Rounding with Combinatorial Arguments ... 31 P. Ejraimidis, P. G. Spirakis 1. Introduction ................................................... 32 2. A Scheduling Problem ......................................... 33 3. Rounding and Deviations ...................................... 36 4. Combinatorial Randomized Rounding .......................... 41 5. Analysis ....................................................... 42 6. Conclusions .................................................... 48 7. Acknowlegements .............................................. 48 References ........................................................ 49 Appendix ......................................................... 50
Statutory Regulation of Casualty Insurance Companies: An Example from Norway with Stochastic Programming Analysis ........................................................ 55 A. Gaivoronski, K. H;Jyland, P. de Lange 1. Introduction ................................................... 56 2. Problem outline ................................................ 58 3. Model description .............................................. 61 4. Numerical analysis ............................................. 71 5. Conclusion ..................................................... 81 References ........................................................ 82
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Option pricing in a world with arbitrage .................... 87 X. Guo, 1. Shepp 1. Introduction ................................................... 87 2. Option pricing under the new model ........................... 90
