Simplified models for multi-criteria decision analysis under uncertainty

Includes abstract.Includes bibliographical references.When facilitating decisions in which some performance evaluations are uncertain, a decision must be taken about how this uncertainty is to be modelled. This involves, in part, choosing an uncertainty format {a way of representing the possible outcomes that may occur. It seems reasonable to suggest {and is an aim of the thesis to show {that the choice of how uncertain quantities are represented will exert some influence over the decision-making process and the final decision taken. Many models exist for multi-criteria decision analysis (MCDA) under conditions of uncertainty; perhaps the most well-known are those based on multi-attribute utility theory [MAUT, e.g. 147], which uses probability distributions to represent uncertainty. The great strength of MAUT is its axiomatic foundation, but even in its simplest form its practical implementation is formidable, and although there are several practical applications of MAUT reported in the literature [e.g. 39, 270] the number is small relative to its theoretical standing. Practical applications often use simpler decision models to aid decision making under uncertainty, based on uncertainty formats that `simplify' the full probability distributions (e.g. using expected values, variances, quantiles, etc). The aim of this thesis is to identify decision models associated with these `simplified' uncertainty formats and to evaluate the potential usefulness of these models as decision aids for problems involving uncertainty. It is hoped that doing so provides some guidance to practitioners about the types of models that may be used for uncertain decision making. The performance of simplified models is evaluated using three distinct methodological approaches {computer simulation, `laboratory' choice experiments, and real-world applications of decision analysis {in the hope of providing an integrated assessment. Chapter 3 generates a number of hypothetical decision problems by simulation, and within each problem simulates the hypothetical application of MAUT and various simplified decision models. The findings allow one to assess how the simplification of MAUT models might impact results, but do not provide any general conclusions because they are based on hypothetical decision problems and cannot evaluate practical issues like ease-of-use or the ability to generate insight that are critical to good decision aid. Chapter 4 addresses some of these limitations by reporting an experimental study consisting of choice tasks presented to numerate but unfacilitated participants. Tasks involved subjects selecting one from a set of five alternatives with uncertain attribute evaluations, with the format used to represent uncertainty and the number of objectives for the choice varied as part of the experimental design. The study is limited by the focus on descriptive rather than real prescriptive decision making, but has implications for prescriptive decision making practice in that natural tendencies are identified which may need to be overcome in the course of a prescriptive analysis

New Challenges in Neutrosophic Theory and Applications

Neutrosophic theory has representatives on all continents and, therefore, it can be said to be a universal theory. On the other hand, according to the three volumes of “The Encyclopedia of Neutrosophic Researchers” (2016, 2018, 2019), plus numerous others not yet included in Encyclopedia book series, about 1200 researchers from 73 countries have applied both the neutrosophic theory and method. Neutrosophic theory was founded by Professor Florentin Smarandache in 1998; it constitutes further generalization of fuzzy and intuitionistic fuzzy theories. The key distinction between the neutrosophic set/logic and other types of sets/logics lies in the introduction of the degree of indeterminacy/neutrality (I) as an independent component in the neutrosophic set. Thus, neutrosophic theory involves the degree of membership-truth (T), the degree of indeterminacy (I), and the degree of non-membership-falsehood (F). In recent years, the field of neutrosophic set, logic, measure, probability and statistics, precalculus and calculus, etc., and their applications in multiple fields have been extended and applied in various fields, such as communication, management, and information technology. We believe that this book serves as useful guidance for learning about the current progress in neutrosophic theories. In total, 22 studies have been presented and reflect the call of the thematic vision. The contents of each study included in the volume are briefly described as follows. The first contribution, authored by Wadei Al-Omeri and Saeid Jafari, addresses the concept of generalized neutrosophic pre-closed sets and generalized neutrosophic pre-open sets in neutrosophic topological spaces. In the article “Design of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distribution”, the authors Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, and Abdur Razzaque Mughal discuss the use of probability distribution function of Birnbaum–Saunders distribution as a proportion of defective items and the acceptance probability in a fuzzy environment. Further, the authors Derya Bakbak, Vakkas Uluc¸ay, and Memet S¸ahin present the “Neutrosophic Soft Expert Multiset and Their Application to Multiple Criteria Decision Making” together with several operations defined for them and their important algebraic properties. In “Neutrosophic Multigroups and Applications”, Vakkas Uluc¸ay and Memet S¸ahin propose an algebraic structure on neutrosophic multisets called neutrosophic multigroups, deriving their basic properties and giving some applications to group theory. Changxing Fan, Jun Ye, Sheng Feng, En Fan, and Keli Hu introduce the “Multi-Criteria Decision-Making Method Using Heronian Mean Operators under a Bipolar Neutrosophic Environment” and test the effectiveness of their new methods. Another decision-making study upon an everyday life issue which empowered us to organize the key objective of the industry developing is given in “Neutrosophic Cubic Einstein Hybrid Geometric Aggregation Operators with Application in Prioritization Using Multiple Attribute Decision-Making Method” written by Khaleed Alhazaymeh, Muhammad Gulistan, Majid Khan, and Seifedine Kadry

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Discrete Mathematics and Symmetry

Some of the most beautiful studies in Mathematics are related to Symmetry and Geometry. For this reason, we select here some contributions about such aspects and Discrete Geometry. As we know, Symmetry in a system means invariance of its elements under conditions of transformations. When we consider network structures, symmetry means invariance of adjacency of nodes under the permutations of node set. The graph isomorphism is an equivalence relation on the set of graphs. Therefore, it partitions the class of all graphs into equivalence classes. The underlying idea of isomorphism is that some objects have the same structure if we omit the individual character of their components. A set of graphs isomorphic to each other is denominated as an isomorphism class of graphs. The automorphism of a graph will be an isomorphism from G onto itself. The family of all automorphisms of a graph G is a permutation group

Symmetric and Asymmetric Data in Solution Models

This book is a Printed Edition of the Special Issue that covers research on symmetric and asymmetric data that occur in real-life problems. We invited authors to submit their theoretical or experimental research to present engineering and economic problem solution models that deal with symmetry or asymmetry of different data types. The Special Issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, seventeen papers were accepted and published. The authors proposed different solution models, mainly covering uncertain data in multicriteria decision-making (MCDM) problems as complex tools to balance the symmetry between goals, risks, and constraints to cope with the complicated problems in engineering or management. Therefore, we invite researchers interested in the topics to read the papers provided in the book

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B

Socio-Economic Assessment of Fusion Energy Research, Development, Demonstration and Deployment Programme

Providing safe, clean and affordable energy supply is essential for meeting the basic needs of human society and for supporting economic growth. From the historical perspective, the constantly growing energy use was one of the main factors, which drove the industrialised countries to the current level of prosperity. Meanwhile, in recent decades, the issue of global energy security became a topic of increasing concern in the international policy agenda. On the one hand, the world is facing the problem of exhaustion of most convenient and cheep fuel reserves. The situation is becoming worse, because of the constantly growing demand in developing countries, and the oligopolistic behaviour of major energy exporting countries. On the other hand, the society is becoming more and more sensitive to the environmental pollution problems, caused by the excessive consumption of fossil fuels. In the face of energy security challenge, national governments ought to implement adequate strategies aimed at liberalisation of energy markets, diversification of energy supply mix, enhancement of energy efficiency, encouragement of investments in energy infrastructures, and promotion of innovation in energy sector. In a longer term perspective, the latter point becomes increasingly important, because the world is relying currently on the consumption of non-renewable fossil fuels, and the development of new safe, clean and resource unconstraint energy technologies is vitally needed. In line with this strategy, the major world economies pursue the joint R&D programme on thermonuclear Fusion technology, which represents numerous advantages due to its inherent safety, avoidance of CO2 emissions, relatively small environmental impact, abundance and world-wide uniform distribution of fuel resources. Considering the importance of the projected environmental and economic benefits of Fusion, the questions are raised whether the current level of financial support is sufficient, and what could be the optimal strategy to proceed with the demonstration of Fusion technology, given the time span and potential risks of Fusion RDDD programme. To put these questions into the context, one has to consider the current trends in energy R&D funding, which has seen a drastic decline ( ~50%) over the last three decades. The liberalisation of energy sector poses additional problem due to the fact that free markets partially failure to provide public goods, such as basic science and R&D, because of the so-called spillover effects meaning that the firms are not able to appropriate the integral results of their R&D investments. Regarding the thermonuclear Fusion technology, the decision makers responsible for national energy policies and allocation of public R&D funds may face the following specific questions: What is the expected net socio-economic payoff (social rate of return) of Fusion R&D programme, including both internal and external costs and benefits? What are the reasonable economic arguments that could justify the increase in public funding of the ongoing and future Fusion R&D activities and would stimulate greater involvement of the private sector? What additional value can be obtained through undertaking a more ambitious Fusion R&D programme (accelerated development path), which requires bigger number of experimental facilities, increased funding, and more intense overall efforts of international scientific and industrial community? In order to provide sound arguments for policymakers seeking to optimise public R&D funding, a robust socio-economic evaluation of the whole Fusion research, development, demonstration and deployment (RDDD) programme is needed. At the present stage, prospective analyses of Fusion technology have been emphasised mainly on the investigation of technological issues, estimation of the direct costs of Fusion power and analysis of its potential role in future energy systems. Meanwhile, methodological tools and practical studies aiming at a more comprehensive socio-economic assessment of global long-term energy R&D programmes, such as Fusion, are still incomplete. The primary difficulty concerns the evaluation of positive externalities that may reveal through different types of spillover effects, including but not limited to knowledge, network and market spillovers. While the presence of these effects has been identified in the economic theory and confirmed by empirical studies, their quantitative analysis in the specific case of large scale energy R&D programmes represents some methodological lacuna and deserves further investigation. Another problem relates to the methodology of cost-benefit analysis, which oftentimes ignores the hidden value of R&D projects arising due to the possible flexibility in managerial decisions. In fact, throughout the course of any R&D project, its prospective cash-flows can be significantly improved by pro-active management of different implementation stages, e.g. expanding the production, if market conditions are favourable, or abandoning, if R&D process appears to be unproductive. As a result, the strategic value of any R&D project normally exceeds its net present value (NPV) calculated with the traditional discounted cash flow (DCF) method. Although this strategic approach to capital budgeting, known as Real Options, has been propagated recently in several publications dealing with appraisal of lumpy irreversible investments, its practical application in the context of Fusion RDDD programme has not been mastered yet to the required extent. A particular challenge consists in the need for adequate treatment of different types of uncertainty in the model structure, parameters and input data. Accordingly, the main objective of this thesis consists in complementing the existing studies with an in-depth analysis of the positive externalities (spillover benefits) of Fusion RDDD programme and calculation of its strategic real options value subject to different managerial strategies throughout demonstration and deployment stages. Net social present value of Fusion RDDD programme and potential impact of Fusion R&D activities on the economic performance of the involved private companies are estimated using an integrated modelling framework, which includes the following components: (1) assessment of technological potential for deployment of Fusion power plants based on the simulation of multi-regional long term electricity supply scenarios with PLANELEC model; (2) economic evaluation of Fusion RDDD programme and analysis of different implementation strategies using Real Options model; (3) estimation of the economic value of spillover benefits from participation in Fusion R&D projects at the microeconomic level with the help of financial evaluation model; (4) strategic evaluation of Fusion RDDD programme, taking into account both spillover benefits and real options value, and policy recommendations