Linear Multiobjective Programming

Zelený, Milan

doi:10.1007/978-3-642-80808-1

Cited by 430 publications

(122 citation statements)

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“…The entropy concept was defined as a measure of uncertainty by Shannon and Weaver (1949). The decision matrix for a MCDM problem comprises a definite quantity of information; entropy can be utilized as an implement in criteria evaluation (Zeleny, 1974;Nijkamp, 1977).…”

Section: Entropy Methodsmentioning

confidence: 99%

An Evaluation of the Financial Performance of REITs in Borsa Istanbul: A Case Study Using the Entropy-Based TOPSIS Method

Islamoğlu¹,

Apan²,

Öztel³

2015

International Journal of Financial Research

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Real Estate Investment Trusts are financial intermediaries which facilitate the provision of finance for real estate properties and thus play a key role in the development of the real estate market. An accredited assessment of financial performance is more vital today as there is increasing competition which poses a risk to maintaining the market share of companies. Therefore, the valuation of companies in terms of liquidity, profitability, turnover and capital structure help managers to take the necessary measures and thus contribute to the soundness of the companies. In this study, a financial analysis of REITs between 2011Q1-2014Q3 within the financial market in Turkey was measured using Entropy based TOPSIS (Technique for Order Preference by Similarity to An Ideal Solution) which is a widely-used Multi-Criteria Decision Making (MCDM) method. According to the empirical results, for all the periods, Avrasya, Akmerkez, Sinpaş, Kiler and İş were found to be the most efficient REITs respectively, whereas, İdealist, Atakule, Alarko, Nurol and Vakıf demonstrated the worst financial performances throughout the whole period.

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Section: Entropy Methodsmentioning

confidence: 99%

An Evaluation of the Financial Performance of REITs in Borsa Istanbul: A Case Study Using the Entropy-Based TOPSIS Method

Islamoğlu¹,

Apan²,

Öztel³

2015

International Journal of Financial Research

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“…Algorithms for computing (characterizing) E are called vector-maximum algorithm (see Evans and Steuer, 1973;Yu, 1974;Zeleny, 1974;Isermann, 1977;Gal, 1977;Ecker, Hegner and Kouada, 1980).…”

Section: Linear Casementioning

confidence: 99%

Methodology and Software for Interactive Decision Support

Lewandowski¹,

Stanchev²

1989

Lecture Notes in Economics and Mathematical Systems

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The workshop was held in Albena, on the Black Sea coast. More than 80 scientists from 15 countries attended the workshop; 50 lectures were presented and 17 computer demonstration sessions took place. This Workshop is one of a series of meetings organized by nASA with the collaboration of scientific institutions from the National Member Organization countries. The previous meetings took place in Austria (1983), Hungary (1984) and the German Democratic Republic (1985). All proceedings of these meetings have been published by Springer Verlag in the series Lecture Notes in Economics and Mathematical Systems.The research on decision support systems has long tradition at nASA. The Institute, being the forum for common research of scientists from East and West, with different cultural backgrounds and different experiences with real life applications of their results, operates the international network of scientific institutions involved in research related to the methodology of decision analysis and decision support systems. The approach to this research assumes high level of synergy between three main components: methodological and theoretical backgrounds, computer implementation of decision support systems and real life applications. This synergy is reflected in the subject of papers presented during the workshop as well as in the structure of the Proceedings which is divided in three main sections.In the first section, Theory and Algorithms for Multiple Criteria Optimization, new theoretical developments in multiple criteria optimization are presented. Tanino presents new approach for application of multiple objective optimization in hierarchical systems, Wierzbicki discusses the relation between simulation and gaming for conflict resolution as well as proposes the interactive framework for supporting this kind of decision problems. The other group of papers addresses purely theoretical questionsNakayama presents recent developments in sensitivity and trade-offs analysis in multiobjective programming, Ramesh and others discuss the degeneracy problem. Finally, several papers are more algorithmic oriented -like paper by Katoh with presentation of new algorithms for bicriteria combinatorial optimization or the paper presenting the reachable set approach by £otov. Finally, Steuer presents the current state-of-the art in the interactive multiple criteria optimization.In the second section, Theory, Methodology and Software for Decision Support Systems, the principles of building decision support systems are presented as well as software IV tools constituting the building components of such systems. Moreover, several papers are devoted to the general methodology of building such systems or present experimental design of systems supporting certain class of decision problems. For example, paper by Makowski presents the HYBRID system for solving dynamic linear multiple criteria problems using the aspiration level paradigm. This system has been used as component of several practical implementations of DSS. Similar nature has ...

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“…(The theory and a number of computer programs for multiobjective linear problems are widely discussed in the literature, e.g. by Evans and Steuer (1973) and Zeleny (1974).) In contrast, nonlinear problem formulations do not add to our understanding of reality and often cannot be solved by standard computerized solution techniques.…”

Section: The Basic Model and Difierent Versionsmentioning

confidence: 99%

Decision Support for Innovation Management: Application to the Lighting Industry.

Beaumont¹,

Haustein²,

Weber³

1985

The Journal of the Operational Research Society

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I n t e r n a t i o n a l I n s t i t u t e f o r A p p l i e d S y s t e m s A n a l y s i s , L a x e n b u r g , A u s t r i a RR-83-29 December 1983 INTERNATIONAL INSTlTUTE FOR APPLIED SYSIXMS ANALYSIS Laxenburg, AustriaInternational Standard Book Number 3-7045-0050-5Research Reports, which record research conducted a t IIASA, a r e independently reviewed before publication. However, t h e views and opinions they express a r e not necessarily those of t h e Institute or t h e National Member Organizations t h a t support it.Copyright O 1983 International Institute for Applied Systems Analysis All rights reserved. No part of this publication may be reproduced or transmitted in any form o r by any means, electronic or mechanical, including photocopy, recording, or any information storage o r retrieval system, without permission in writing from the publisher. Cover design by Anka JamesPrinted by Novographic, Vienna. Austria In today's turbulent economic environment, every decision affecting t h e development of industry necessarily carries a n increased risk t h a t t h e anticipated economic and social goals will not be achieved. The description of decision making does not always include t h e notion of risk. Sometimes t h e "volatility of cost factors" or changing economies of scale (innovation being t h e primary reason for t h e change) are held responsible for uncertainty about future development. These phenomena are also used t o explain t h e decline in capital formation and in decisions to invest t h a t we a r e currently witnessing.The economic and decision sciences are trying to cope with this situation by devising more sophisticated methods and procedures for supporting decision making. This Research Report reviews some methods t h a t a r e applicable t o t h e analysis of innovation patterns, with t h e a i m of basing t h e necessary decisions on more sound reasoning. The report t h e n describes t h e application of some of these methods to innovation management i n t h e lighting industry. I t is hoped t h a t their application will result in better decisions being made in t h e allocation of resources for innovation. DECISION SUPPORT FOR INNOVATION MANAGEMENT: APPLICATION TO THE LIGHTING INDUSTRY Heinz-Dieter Haustein and Mathias Weber h t e r n a t i o n a l I n s t i t u t e f o r Applied S y s t e m s Analysis, L a z e n b u r g , A u s t r i a Making d e c i s i o n s a b o u t r e s o u r c e a l l o c a t i o n f o r f u t u r e i n n o v a t i o n s is a c h a l l e n g i n g t a s k in b o t h p l a n n e d a n d m a r k e t e c o n o m i e s . Not o n l y c a n s u c h d e c i s i o n s n o t be r e v e r s e d w i t h o u t considerable l o s s of efficiency, b u t t h e decis i o n m a k e r g e n e r a l l y f a c e s a n u m b e r of conflicting objectives. In this r e p o r t the a u t h o r s t r y t o c o m b i n e t w o d i s c i p l i n e s that have b e e n evolving i n d e p e nd e n t l y f o r a l o n g t i m e : i n n o v a t i o n t h e o r y a n d d e c i s i o n theo...

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Linear Multiobjective Programming

Cited by 430 publications

References 0 publications

An Evaluation of the Financial Performance of REITs in Borsa Istanbul: A Case Study Using the Entropy-Based TOPSIS Method

An Evaluation of the Financial Performance of REITs in Borsa Istanbul: A Case Study Using the Entropy-Based TOPSIS Method

Methodology and Software for Interactive Decision Support

Decision Support for Innovation Management: Application to the Lighting Industry.

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