Financial Decision Making Using Computational Intelligence
Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now
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Aims and Scope Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics, engineering, medicine, economics, and other sciences. The series Springer Optimization and Its Applications publishes undergraduate and graduate textbooks, monographs and state-of-the-art expository work that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization (convex and nonconvex), network flow problems, stochastic optimization, optimal control, discrete optimization, multi-objective programming, description of software packages, approximation techniques and heuristic approaches.
For further volumes: http://www.springer.com/series/7393
Michael Doumpos • Constantin Zopounidis Panos M. Pardalos Editors
Financial Decision Making Using Computational Intelligence
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Editors Michael Doumpos Department of Production Engineering & Management Technical University of Crete University Campus Chania, Greece
Constantin Zopounidis Department of Production Engineering & Management Technical University of Crete University Campus Chania, Greece
Panos M. Pardalos Center for Applied Optimization ISE Department University of Florida Gainesville, FL, USA and Laboratory of Algorithms and Technologies for Networks Analysis (LATNA) National Research University Higher School of Economics Moscow, Russia
ISSN 1931-6828 ISBN 978-1-4614-3772-7 ISBN 978-1-4614-3773-4 (eBook) DOI 10.1007/978-1-4614-3773-4 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2012942084 © Springer Science+Business Media New York 2012 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use
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