Multiple Criteria Decision Aid Methods, Examples and Python Impleme
Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is g
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Jason Papathanasiou · Nikolaos Ploskas
Multiple Criteria Decision Aid Methods, Examples and Python Implementations
Springer Optimization and Its Applications Volume 136 Managing Editor: Panos M. Pardalos, University of Florida Editor-Combinatorial Optimization: Ding-Zhu Du, University of Texas at Dallas Advisory Board: J. Birge, University of Chicago S. Butenko, Texas A & M University F. Giannessi, University of Pisa S. Rebennack, Karlsruhe Institute of Technology T. Terlaky, Lehigh University Y. Ye, Stanford University
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 aims to publish state-ofthe-art expository works (monographs, contributed volumes, textbooks) 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.
More information about this series at http://www.springer.com/series/7393
Jason Papathanasiou • Nikolaos Ploskas
Multiple Criteria Decision Aid Methods, Examples and Python Implementations
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Jason Papathanasiou Department of Business Administration University of Macedonia Thessaloniki, Greece
Nikolaos Ploskas Carnegie Mellon University Pittsburgh, PA, USA
ISSN 1931-6828 ISSN 1931-6836 (electronic) Springer Optimization and Its Applications ISBN 978-3-319-91646-0 ISBN 978-3-319-91648-4 (eBook) https://doi.org/10.1007/978-3-319-91648-4 Library of Congress Control Number: 2018942889 Mathematics Subject Classification: 90, 90C29, 90C70, 90C90 © Springer International Publishing AG, part of Springer Nature 2018 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. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the rel
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