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Decision Making, Classical and Quantum Optimization Methods

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 16603

Special Issue Editors


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Guest Editor
Faculty of Economics and Finance, University of Bialystok, 15-062 Bialystok, Poland
Interests: negotiation; negotiation support; multicriteria decision making; fuzzy multicriteria decision making
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Operations Research, College of Informatics and Communication, University of Economics in Katowice, ul. Bogucicka 3, 40-287 Katowice, Poland
Interests: quantum economics; quantum games; quantum communication
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of technology opens up new possibilities of using it to optimize decision making. Methods based on artificial intelligence and machine learning will in the future set the standards for optimization of decisions in key areas of the economy and human life.

Advances in quantum information processing also open up new opportunities. Quantum methods allow achieving new ways of strategy randomization and offer a classically unavailable level of information security.

The aim of the project is to explore various theoretical methods of decision optimization based both on the classical and quantum approach.

The scope of the project includes the development of tools and techniques to optimize decisions by:

  • A scoring system for negotiation analysis and building a negotiation template and its rating system that reflect the structure of the negotiation problem and the negotiator’s preferences;
  • Game theory and the application of fair-share and matching algorithms (Shapley, Roth);
  • Quantum game theory models to obtain more Pareto-efficient equilibria in interactive decision making;
  • Bayesian methods for decision optimization;
  • Entropy-based measures in machine learning;
  • Fuzzy multicriteria decision analysis.

Prof. Dr. Ewa Roszkowska
Prof. Dr. Marek Szopa
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • decision optimization
  • game theory
  • quantum game theory
  • negotiation
  • machine learning
  • Pareto efficiency

Published Papers (9 papers)

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Research

12 pages, 254 KiB  
Article
From Goal Programming for Continuous Multi-Criteria Optimization to the Target Decision Rule for Mixed Uncertain Problems
by Helena Gaspars-Wieloch
Entropy 2022, 24(1), 51; https://doi.org/10.3390/e24010051 - 28 Dec 2021
Cited by 3 | Viewed by 1800
Abstract
Goal programming (GP) is applied to the discrete and continuous version of multi-criteria optimization. Recently, some essential analogies between multi-criteria decision making under certainty (M-DMC) and scenario-based one-criterion decision making under uncertainty (1-DMU) have been revealed in the literature. The aforementioned similarities allow [...] Read more.
Goal programming (GP) is applied to the discrete and continuous version of multi-criteria optimization. Recently, some essential analogies between multi-criteria decision making under certainty (M-DMC) and scenario-based one-criterion decision making under uncertainty (1-DMU) have been revealed in the literature. The aforementioned similarities allow the adjustment of GP to an entirely new domain. The aim of the paper is to create a new decision rule for mixed uncertain problems on the basis of the GP methodology. The procedure can be used by pessimists, optimists and moderate decision makers. It is designed for one-shot decisions. One of the significant advantages of the novel approach is related to the possibility to analyze neutral criteria, which are not directly taken into account in existing classical procedures developed for 1-DMU. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
23 pages, 1044 KiB  
Article
Shapley-Based Estimation of Company Value—Concept, Algorithms and Parameters
by Jacek Mercik, Barbara Gładysz, Izabella Stach and Jochen Staudacher
Entropy 2021, 23(12), 1598; https://doi.org/10.3390/e23121598 - 28 Nov 2021
Cited by 2 | Viewed by 1618
Abstract
The aim of the article is to propose a new method of valuation of a company, considering its ownership relations with other companies. For this purpose, the concept of the Shapley value from cooperative game theory is used as the basis for assessing [...] Read more.
The aim of the article is to propose a new method of valuation of a company, considering its ownership relations with other companies. For this purpose, the concept of the Shapley value from cooperative game theory is used as the basis for assessing such dependent companies. The paper presents proposals for Shapley value calculation algorithms for our model. We expand our model by discussing personal relations in addition to ownership relations and point out how intuitionistic fuzzy sets may be helpful in this context. As a result, we propose two new expanded models. In the first probabilistic model, we apply Pearson’s correlation coefficient, in the second, we use a correlation coefficient between intuitionistic fuzzy sets to determine the personal relationships. Finally, we present and interpret results for a real-world economic network with 17 companies. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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20 pages, 573 KiB  
Article
Interactive Multiobjective Procedure for Mixed Problems and Its Application to Capacity Planning
by Maciej Nowak, Tadeusz Trzaskalik and Sebastian Sitarz
Entropy 2021, 23(10), 1243; https://doi.org/10.3390/e23101243 - 24 Sep 2021
Cited by 1 | Viewed by 1102
Abstract
A problem that appears in many decision models is that of the simultaneous occurrence of deterministic, stochastic, and fuzzy values in the set of multidimensional evaluations. Such problems will be called mixed problems. They lead to the formulation of optimization problems in ordered [...] Read more.
A problem that appears in many decision models is that of the simultaneous occurrence of deterministic, stochastic, and fuzzy values in the set of multidimensional evaluations. Such problems will be called mixed problems. They lead to the formulation of optimization problems in ordered structures and their scalarization. The aim of the paper is to present an interactive procedure with trade-offs for mixed problems, which helps the decision-maker to make a final decision. Its basic advantage consists of simplicity: after having obtained the solution proposed, the decision-maker should determine whether it is satisfactory and if not, how it should be improved by indicating the criteria whose values should be improved, the criteria whose values cannot be made worse, and the criteria whose values can be made worse. The procedure is applied in solving capacity planning treated as a mixed dynamic programming problem. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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29 pages, 422 KiB  
Article
On the Statistical Discrepancy and Affinity of Priority Vector Heuristics in Pairwise-Comparison-Based Methods
by Pawel Tadeusz Kazibudzki
Entropy 2021, 23(9), 1150; https://doi.org/10.3390/e23091150 - 01 Sep 2021
Cited by 4 | Viewed by 1751
Abstract
There are numerous priority deriving methods (PDMs) for pairwise-comparison-based (PCB) problems. They are often examined within the Analytic Hierarchy Process (AHP), which applies the Principal Right Eigenvalue Method (PREV) in the process of prioritizing alternatives. It is known that when decision makers (DMs) [...] Read more.
There are numerous priority deriving methods (PDMs) for pairwise-comparison-based (PCB) problems. They are often examined within the Analytic Hierarchy Process (AHP), which applies the Principal Right Eigenvalue Method (PREV) in the process of prioritizing alternatives. It is known that when decision makers (DMs) are consistent with their preferences when making evaluations concerning various decision options, all available PDMs result in the same priority vector (PV). However, when the evaluations of DMs are inconsistent and their preferences concerning alternative solutions to a particular problem are not transitive (cardinally), the outcomes are often different. This research study examines selected PDMs in relation to their ranking credibility, which is assessed by relevant statistical measures. These measures determine the approximation quality of the selected PDMs. The examined estimates refer to the inconsistency of various Pairwise Comparison Matrices (PCMs)—i.e., W = (wij), wij > 0, where i, j = 1,…, n—which are obtained during the pairwise comparison simulation process examined with the application of Wolfram’s Mathematica Software. Thus, theoretical considerations are accompanied by Monte Carlo simulations that apply various scenarios for the PCM perturbation process and are designed for hypothetical three-level AHP frameworks. The examination results show the similarities and discrepancies among the examined PDMs from the perspective of their quality, which enriches the state of knowledge about the examined PCB prioritization methodology and provides further prospective opportunities. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
13 pages, 1426 KiB  
Article
Market Choices Driven by Reference Groups: A Comparison of Analytical and Simulation Results on Random Networks
by Michał Ramsza
Entropy 2021, 23(8), 1007; https://doi.org/10.3390/e23081007 - 01 Aug 2021
Viewed by 1592
Abstract
The present paper reports simulation results for a simple model of reference group influence on market choices, e.g., brand selection. The model was simulated on three types of random graphs, Erdos–Renyi, Barabasi–Albert, and Watts–Strogatz. The estimates of equilibria based on the simulation results [...] Read more.
The present paper reports simulation results for a simple model of reference group influence on market choices, e.g., brand selection. The model was simulated on three types of random graphs, Erdos–Renyi, Barabasi–Albert, and Watts–Strogatz. The estimates of equilibria based on the simulation results were compared to the equilibria of the theoretical model. It was verified that the simulations exhibited the same qualitative behavior as the theoretical model, and for graphs with high connectivity and low clustering, the quantitative predictions offered a viable approximation. These results allowed extending the results from the simple theoretical model to networks. Thus, by increasing the positive response towards the reference group, the third party may create a bistable situation with two equilibria at which respective brands dominate the market. This task is easier for large reference groups. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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19 pages, 868 KiB  
Article
Fuzzy Representation of Principal’s Preferences in Inspire Negotiation Support System
by Krzysztof Piasecki, Ewa Roszkowska, Tomasz Wachowicz, Marzena Filipowicz-Chomko and Anna Łyczkowska-Hanćkowiak
Entropy 2021, 23(8), 981; https://doi.org/10.3390/e23080981 - 29 Jul 2021
Cited by 2 | Viewed by 1723
Abstract
We consider the negotiation problem, in which an agent negotiates on behalf of a principal. Our considerations are focused on the Inspire negotiation support system in which the principal’s preferences are visualised by circles. In this way, the principal describes the importance of [...] Read more.
We consider the negotiation problem, in which an agent negotiates on behalf of a principal. Our considerations are focused on the Inspire negotiation support system in which the principal’s preferences are visualised by circles. In this way, the principal describes the importance of each negotiation issue and the relative utility of each considered option. The paper proposes how this preference information may be implemented by the agent for determining a scoring function used to support decisions throughout the negotiation process. The starting point of our considerations is a discussion regarding the visualisation of the principal’s preferences. We assume here that the importance of each issue and the utility of each option increases with the size of the circle representing them. The imprecise meaning of the notion of “circle size” implies that in a considered case, the utility of an option should be evaluated by a fuzzy number. The proposed utility fuzzification is justified by a simple analysis of results obtained from the empirical prenegotiation experiment. A novel method is proposed to determine trapezoidal fuzzy numbers, which evaluates an option’s utility using a series of answers given by the participants of the experiment. The utilities obtained this way are applied to determine the fuzzy scoring function for an agent. By determining such a common generalised fuzzy scoring system, our approach helps agents handle the differences in human cognitive processes associated with understanding the principal’s preferences. This work is the first approach to fuzzification of the preferences in the Inspire negotiation support system. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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22 pages, 1853 KiB  
Article
Reducing Cognitive Effort in Scoring Negotiation Space Using the Fuzzy Clustering Model
by Marzena Filipowicz-Chomko, Rafał Mierzwiak, Marcin Nowak, Ewa Roszkowska and Tomasz Wachowicz
Entropy 2021, 23(6), 752; https://doi.org/10.3390/e23060752 - 15 Jun 2021
Cited by 1 | Viewed by 1947
Abstract
Negotiation scoring systems are fundamental tools used in negotiation support to facilitate parties searching for negotiation agreement and analyzing its efficiency and fairness. Such a scoring system is obtained in prenegotiation by implementing selected multiple criteria decision-aiding methods to elicit the negotiator’s preferences [...] Read more.
Negotiation scoring systems are fundamental tools used in negotiation support to facilitate parties searching for negotiation agreement and analyzing its efficiency and fairness. Such a scoring system is obtained in prenegotiation by implementing selected multiple criteria decision-aiding methods to elicit the negotiator’s preferences precisely and ensure that the support is reliable. However, the methods classically used in the preference elicitation require much cognitive effort from the negotiators, and hence, do not prevent them from using heuristics and making simple errors that result in inaccurate scoring systems. This paper aims to develop an alternative tool that allows scoring the negotiation offers by implementing a sorting approach and the reference set of limiting profiles defined individually by the negotiators in the form of complete packages. These limiting profiles are evaluated holistically and verbally by the negotiator. Then the fuzzy decision model is built that uses the notion of increasing the preference granularity by introducing a series of limiting sub-profiles for corresponding sub-categories of offers. This process is performed automatically by the support algorithm and does not require any additional preferential information from the negotiator. A new method of generating reference fuzzy scores to allow a detailed assignment of any negotiation offer from feasible negotiation space to clusters and sub-clusters is proposed. Finally, the efficient frontier and Nash’s fair division are used to identify the recommended packages for negotiation in the bargaining phase. This new approach allows negotiators to obtain economically efficient, fair, balanced, and reciprocated agreements while minimizing information needs and effort. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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13 pages, 632 KiB  
Article
Non-Classical Rules in Quantum Games
by Piotr Frąckiewicz
Entropy 2021, 23(5), 604; https://doi.org/10.3390/e23050604 - 13 May 2021
Cited by 3 | Viewed by 1310
Abstract
Over the last twenty years, quantum game theory has given us many ideas of how quantum games could be played. One of the most prominent ideas in the field is a model of quantum playing bimatrix games introduced by J. Eisert, M. Wilkens [...] Read more.
Over the last twenty years, quantum game theory has given us many ideas of how quantum games could be played. One of the most prominent ideas in the field is a model of quantum playing bimatrix games introduced by J. Eisert, M. Wilkens and M. Lewenstein. The scheme assumes that players’ strategies are unitary operations and the players act on the maximally entangled two-qubit state. The quantum nature of the scheme has been under discussion since the article by Eisert et al. came out. The aim of our paper was to identify some of non-classical features of the quantum scheme. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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14 pages, 1228 KiB  
Article
Efficiency of Classical and Quantum Games Equilibria
by Marek Szopa
Entropy 2021, 23(5), 506; https://doi.org/10.3390/e23050506 - 22 Apr 2021
Cited by 12 | Viewed by 2287
Abstract
Nash equilibria and correlated equilibria of classical and quantum games are investigated in the context of their Pareto efficiency. The examples of the prisoner’s dilemma, battle of the sexes and the game of chicken are studied. Correlated equilibria usually improve Nash equilibria of [...] Read more.
Nash equilibria and correlated equilibria of classical and quantum games are investigated in the context of their Pareto efficiency. The examples of the prisoner’s dilemma, battle of the sexes and the game of chicken are studied. Correlated equilibria usually improve Nash equilibria of games but require a trusted correlation device susceptible to manipulation. The quantum extension of these games in the Eisert–Wilkens–Lewenstein formalism and the Frąckiewicz–Pykacz parameterization is analyzed. It is shown that the Nash equilibria of these games in quantum mixed Pauli strategies are closer to Pareto optimal results than their classical counter-parts. The relationship of mixed Pauli strategies equilibria and correlated equilibria is also studied. Full article
(This article belongs to the Special Issue Decision Making, Classical and Quantum Optimization Methods)
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