scholarly journals Investment Opportunities Identification Based on Macroeconomic Development, the Multiple Criteria Decision Approach

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 827 ◽  
Author(s):  
Veronika Mitkova ◽  
Vladimír Mlynarovič
Keyword(s):  
Multiple Criteria Decision Making ◽  
Investment Strategy ◽  
Multiple Criteria ◽  
Optimization Approach ◽  
Government Bond ◽  
Government Bonds ◽  
Promethee Ii ◽  
Symmetry Approach ◽  
Investment Opportunities ◽  
Criteria Weights

The aim of this work is to develop a “learning model” which outranks countries according to their confrontation of historical macroeconomic indicators for a given period of time with the spreads at the end of that time and to formulate a forward-looking investment strategy regarding government bonds for the following time period. The mechanism of identifying investment opportunities among government bonds is based on the multiple criteria decision making technique, and we look to the Promethee II method as a symmetry approach to country ordering. The spread is defined as the difference between the yield to maturity of the 10-year government bond of a country and the Germany government bond with the same maturity. In this paper, an optimization approach based on three models is developed to find the weights of importance for macroeconomic characteristics, together with a sensitivity analysis on changes in these characteristics. The method was applied to 17 European countries characterized by 16 macroeconomic characteristics. The originality of this paper lies in the two-stage approach to the investment strategy construction based on criteria weights optimization with stability intervals for their values.

scholarly journals A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Criteria Decision Making ◽  
Grey System Theory ◽  
Multiple Criteria ◽  
Decision Making Process ◽  
Grey System ◽  
Criteria Weights

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.

scholarly journals Criteria weights balancing using Kemeny median

2014 ◽  
Vol 55 ◽  
Author(s):  
Aleksandras Krylovas ◽  
Natalja Kosareva
Keyword(s):  
Decision Making ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Criteria Weights ◽  
Conditional Optimization

The proposed in the article weights balancing approach enables to solve multiple criteria decision making tasks for the cases when objects are estimated by the two or more groups of the criteria which are not quantitatively compatible with each other. Criteria weights are being balanced by solving conditional optimization problems. The conditions for the certain optimization problem are determined by the construction of Kemeny median.

Area-based harvest scheduling and allocation of forest land using methods for multiple-criteria decision making

1993 ◽  
Vol 23 (2) ◽  
pp. 151-158 ◽  
Author(s):  
Andrew F. Howard ◽  
John D. Nelson
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Multiple Objectives ◽  
Multiple Criteria ◽  
Land Allocation ◽  
Harvest Scheduling ◽  
Simultaneous Solution ◽  
Forest Land ◽  
Criteria Weights ◽  
Explicit Consideration

A new, deterministic methodology for simultaneous solution of the scheduling and allocation problems based on methods developed for multiple-criteria decision making is proposed. Seven steps for the use of multiple-criteria decision making techniques are reviewed, and the details of the proposed application to area-based harvest scheduling and forest land allocation are presented. The approach was used in a sample, hypothetical problem in which harvest schedules and allocations were developed for three competitors, using three decision criteria and two sets of criteria weights. The results indicate that the new method provides an effective alternative to traditional methods and offers numerous advantages including the explicit consideration of multiple objectives.

New Method for Solving a General Multiple Criteria Decision-Making Problem Under Risk in Fuzzy Environment

2016 ◽  
Vol 15 (05) ◽  
pp. 1157-1179 ◽  
Author(s):  
N. Thillaigovindan ◽  
S. Anita Shanthi ◽  
J. Vadivel Naidu
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Fuzzy Soft Set ◽  
Score Functions ◽  
Fuzzy Environment ◽  
Criterion Weight ◽  
Decision Making Problem ◽  
Criteria Weights ◽  
Interval Valued

This paper considers a multiple criteria decision-making (MCDM) problem under risk in fuzzy environment in its general form. There are m alternatives which need to be ranked on the basis of a set of n criteria. The alternatives and the criteria are evaluated based on a set of l characteristics. The entire data is presented in the form of interval valued intuitionistic fuzzy soft set of root type. In addition each criterion is assigned a subjective criterion weight based on expert’s evaluation and each characteristic is assigned a probability weight on the basis of decision maker’s knowlege and understanding of the importance of the characteristic. This problem may be called as a MCDM problem under risk in fuzzy environment in its general form. A method for ranking the alternatives using the new score functions, prospect theory and method of determining the optimum criteria weights is explained. An algorithm is developed for this purpose and its working illustrated with a suitable example.

Artificial Intelligence in Stochastic Multiple-Criteria Decision Making

2020 ◽  
pp. 957-982
Author(s):  
Hanna Sawicka
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Distribution System ◽  
Multiple Criteria Decision Making ◽  
Pharmaceutical Products ◽  
Multiple Criteria ◽  
Distribution Centers ◽  
Promethee Ii ◽  
The Core ◽  
Mcdm Method

This chapter presents the concept of stochastic multiple criteria decision making (MCDM) method to solve complex ranking decision problems. This approach is composed of three main areas of research, i.e. classical MCDM, probability theory and classification method. The most important steps of the idea are characterized and specific features of the applied methods are briefly presented. The application of Electre III combined with probability theory, and Promethee II combined with Bayes classifier are described in details. Two case studies of stochastic multiple criteria decision making are presented. The first one shows the distribution system of electrotechnical products, composed of 24 distribution centers (DC), while the core business of the second one is the production and warehousing of pharmaceutical products. Based on the application of presented stochastic MCDM method, different ways of improvements of these complex systems are proposed and the final i.e. the best paths of changes are recommended.

Artificial Intelligence in Stochastic Multiple Criteria Decision Making

2017 ◽  
pp. 315-340
Author(s):  
Hanna Sawicka
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Distribution System ◽  
Multiple Criteria Decision Making ◽  
Pharmaceutical Products ◽  
Multiple Criteria ◽  
Distribution Centers ◽  
Promethee Ii ◽  
The Core ◽  
Mcdm Method

This chapter presents the concept of stochastic multiple criteria decision making (MCDM) method to solve complex ranking decision problems. This approach is composed of three main areas of research, i.e. classical MCDM, probability theory and classification method. The most important steps of the idea are characterized and specific features of the applied methods are briefly presented. The application of Electre III combined with probability theory, and Promethee II combined with Bayes classifier are described in details. Two case studies of stochastic multiple criteria decision making are presented. The first one shows the distribution system of electrotechnical products, composed of 24 distribution centers (DC), while the core business of the second one is the production and warehousing of pharmaceutical products. Based on the application of presented stochastic MCDM method, different ways of improvements of these complex systems are proposed and the final i.e. the best paths of changes are recommended.

scholarly journals INVESTMENT PROJECTS EVALUATION BY SIMULATION AND MULTIPLE CRITERIA DECISION AIDING PROCEDURE

2005 ◽  
Vol 11 (3) ◽  
pp. 193-202 ◽  
Author(s):  
Maciej Nowak
Keyword(s):  
Financial Analysis ◽  
Multiple Criteria Decision Making ◽  
Ecological Factors ◽  
Multiple Criteria ◽  
Multiple Criteria Decision Aiding ◽  
Promethee Ii ◽  
Investment Projects ◽  
Decision Aiding ◽  
Decision Making Problem ◽  
The One

The paper considers an investment projects selection problem. The evaluation of each project is usually a multidimensional problem. On the one hand, financial analysis is very important, on the other, however, technical, social, and ecological factors are taken into account too. While financial criteria are usually of quantitative nature, others are often based on qualitative judgments. As the analysis of each project is based on uncertain assumptions, so the problem can be considered as a discrete stochastic multiple criteria decision‐making problem. In this paper simulation, stochastic dominance rules and multiple criteria decision aiding procedure PROMETHEE II are employed for solving such a problem. While simulation technique is used for obtaining financial evaluations of projects, experts’ judgments are taken into account in order to evaluate project with respect to other criteria. Thus, quantitative and qualitative factors are considered in this approach.

Implementing a Cloud-Based Decision Support System in a Private Cloud

2016 ◽  
Vol 8 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Imene Benatia ◽  
Mohamed Ridda Laouar ◽  
Hakim Bendjenna ◽  
Sean B. Eom
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Processing Time ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Promethee Ii ◽  
Urban Project ◽  
The Cost

This paper introduces the architecture and the deployment of a Cloud based decision support system (DSS). The DSS the authors proposed is deployed on a platform Cloud (CloudBees) and managed by the OpenStack infrastructure. The DSS is built on the Cloud Computing architecture with three layers and includes the multiple criteria decision making (MCDM) method PROMETHEE II as well as the procedure of negotiation Hare in order to help the decision makers to select the best urban project. The Cloud based DSS reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility and decrease the cost. The Cloud based multiple criteria DSS the authors designed and implemented has significant advantages. It reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility, and decrease the cost.

An intelligent approach for the evaluation of transformers in a power distribution project

2020 ◽  
Vol 39 (3) ◽  
pp. 4133-4145
Author(s):  
Funda Samanlioglu ◽  
Zeki Ayağ
Keyword(s):  
Power Distribution ◽  
Fuzzy Ahp ◽  
Hybrid Approach ◽  
Multiple Criteria Decision Making ◽  
Preference Ranking ◽  
Analytic Hierarchy ◽  
Promethee Ii ◽  
Order Preference ◽  
Criteria Weights ◽  
Intelligent Approach

In this study, a hybrid approach is presented for the evaluation and selection of transformers in a power distribution project. Ranking transformers and selecting the best among alternatives is a complex multiple criteria decision making (MCDM) problem with various possibly conflicting quantitative and qualitative criteria. In this research, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy Preference Ranking Organization Method for Enriching Evaluations II (hesitant F-PROMETHEE II) are combined to evaluate and rank transformers. In the hesitant fuzzy AHP-PROMETHEE II, hesitant F-AHP is implemented to determine criteria weights and hesitant F-PROMETHEE II is applied to rank transformer alternatives, utilizing obtained criteria weights. An illustrative example is presented to demonstrate the effectiveness and applicability of the proposed approach. In the example, five transformers are evaluated based on twelve criteria by three decision makers (DMs) and best alternative is selected. For comparison analysis, integration of hesitant F-AHP and hesitant fuzzy Technique for Order Preference by Similarity to Ideal Solution (hesitant F-TOPSIS) is used and results are compared.

An Interval Based Score Method for Multiple Criteria Decision Making Problems

2019 ◽  
Vol 18 (05) ◽  
pp. 1667-1687
Author(s):  
S. Saffarzadeh ◽  
A. Hadi-Vencheh ◽  
A. Jamshidi
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Linear Optimization ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Optimization Approach ◽  
Interval Numbers ◽  
Common Set Of Weights ◽  
Score Method ◽  
Linear Programming Problems

In this paper, a linear optimization approach to solve multiple criteria decision making (MCDM) problems is presented. For this purpose, two linear programming problems are proposed in the most favorable and least favorable senses. Then, an overall score as an interval number for each alternative is obtained. The lower bound is the score in the most favorable sense and its upper bound is the performance in the least favorable sense. The order of all alternatives is ranked in descending order in accordance with these interval numbers using the concept of degree of possibility. This study makes three major contributions. First, the proposed method employs linear programming (LP) technique to solve MCDM problems. Second, the common set of weights are utilized to solve the proposed LP models. Finally, the presented approach incorporates the decision maker preferences in decision making process.

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