Group consensus measurement in MADM with multiple preference formats

An approach is proposed for measuring the group consensus in multiple attribute decision-making (MADM) problems with experts’ various preference information on alternatives. In the approach, multiple decision-makers give their preference information on alternatives in different formats. The uniformities and aggregation process with fuzzy majority method are employed to obtain the social fuzzy preference relation on the alternatives. Accordingly, the ranking values of the alternatives are obtained based on the obtained individual expert’s fuzzy preference relation, and the social one. The group consensus can be measured based on the ranking values of the alternatives that are derived from the individual expert’s preference information and the social one. An example of selecting robots is presented as an illustration

Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039 71421001,71910107002,71771037,71874023 71871149Sichuan University sksyl201705 2018hhs-5

MCDA for sustainability assessment – insights to Helmholtz Association activities

The "MCDA for sustainability assessment – insights to Helmholtz Association activities" Working Paper aims to compile and reflect previous and on-going work within the Helmholtz Association related to MCDA, in particular, to present use cases and key methodological aspects. It has a focus on but is not limited to energy technologies and systems and is mainly based on the presentations held at the online workshop “Multi criteria decision analysis for sustainability assessment of energy technologies and systems”. The workshop was organized within the activities of the Helmholtz program ESD Topic 1 "Energy System Transformation" and took place on November 22nd, 2021

Strategic Weight Manipulation in Multiple Attribute Decision Making in an Incomplete Information Context

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In some real-world multiple attribute decision making (MADM) problems, a decision maker can strategically set attribute weights to obtain her/his desired ranking of alternatives, which is called the strategic weight manipulation of the MADM. Sometimes, the attribute weights are given with imprecise or partial information, which is called incomplete information of attribute weights. In this study, we propose the strategic weight manipulation under incomplete information on attributes weights. Then, a series of mixed 0-1 linear programming models (MLPMs) are proposed to derive a strategic weight vector for a desired ranking of an alternative. Finally, a numerical example is used to demonstrate the validity of our models

Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use

International entrepreneurial startups' location under uncertainty through a heterogeneous multi-layer decision-making approach:Evidence and application of an emerging economy

Purpose: Science and technology parks (STPs) have a limited capacity, which can create challenging conditions for applicants. This makes the location selection a multi-criteria decision-making (MCDM) problem to find and apply for the most appropriate STP with the highest accordance with the startup's requirements. This research aims to select the most appropriate STP to locate an international entrepreneurial pharmaceutical startup under uncertainty. Since drugs are generally produced domestically in developing countries such as Iran, the access of pharmaceutical startups to the resources provided by STPs can lead to overcoming competitors and improving the country's health system. Design/methodology/approach: In this research, the factors or attributes effective on startup location were extracted through a two-round Delphi method, which was performed among 15 experts within three groups. Subsequently, the determining factors were used to select the location of a pharmaceutical startup among possible STPs. In this regard, decision-makers were allowed to use different types of numbers to transfer their opinion. Afterward, the heterogeneous weighted aggregated sum product assessment (HWASPAS) method was applied to calculate the score of each alternative and rank them to place the studied startup successfully. Findings: The results indicated that Tehran STP stands in the first place; however, if the decision was made based on single criterion like cost, some other STPs could be preferable, and many managers would lose this choice. Furthermore, the results of the proposed method were close to other popular heterogeneous MCDM approaches. Originality/value: A heterogeneous WASPAS is developed in this article for the first time to enable international entrepreneurs to imply their opinion with various values and linguistic variables to reduce the emphasis on accurate data in an uncertain environment

Architecture value mapping: using fuzzy cognitive maps as a reasoning mechanism for multi-criteria conceptual design evaluation

The conceptual design phase is the most critical phase in the systems engineering life cycle. The design concept chosen during this phase determines the structure and behavior of the system, and consequently, its ability to fulfill its intended function. A good conceptual design is the first step in the development of a successful artifact. However, decision-making during conceptual design is inherently challenging and often unreliable. The conceptual design phase is marked by an ambiguous and imprecise set of requirements, and ill-defined system boundaries. A lack of usable data for design evaluation makes the problem worse. In order to assess a system accurately, it is necessary to capture the relationships between its physical attributes and the stakeholders\u27 value objectives. This research presents a novel conceptual architecture evaluation approach that utilizes attribute-value networks, designated as \u27Architecture Value Maps\u27, to replicate the decision makers\u27 cogitative processes. Ambiguity in the system\u27s overall objectives is reduced hierarchically to reveal a network of criteria that range from the abstract value measures to the design-specific performance measures. A symbolic representation scheme, the 2-Tuple Linguistic Representation is used to integrate different types of information into a common computational format, and Fuzzy Cognitive Maps are utilized as the reasoning engine to quantitatively evaluate potential design concepts. A Linguistic Ordered Weighted Average aggregation operator is used to rank the final alternatives based on the decision makers\u27 risk preferences. The proposed methodology provides systems architects with the capability to exploit the interrelationships between a system\u27s design attributes and the value that stakeholders associate with these attributes, in order to design robust, flexible, and affordable systems --Abstract, page iii

Measuring web service security in the era of Internet of Things

Technologies such as Internet of Things allow small devices to offer web-based services in an open and dynamic networking environments on a massive scale. End users or service consumers face a hard decision over which service to choose among the available ones, as security holds a key in the decision making process. In this paper a base linguistic evaluation set is designed, based on which all the other fuzzy term sets that used for describing security attributes are uniformed and integrated for calculating an overall security value of the services. This work, to the best of our knowledge, is the first practical solution to offer direct comparisons and rankings of network services based on multiple security attributes such as confidentiality, availability, privacy and accountability. We analysed four major cloud service platforms to illustrate the proposed approach

Managing Consistency and Consensus in Group Decision-Making with Incomplete Fuzzy Preference Relations

Group decision-making is a field of decision theory that has many strengths and benefits. It can solve and simplify the most complex and hard decision problems. In addition, it helps decision-makers know more about the problem under study and their preferences. Group decision-making is much harder and complex than individual decision-making since group members may have different preferences regarding the alternatives, making it difficult to reach a consensus. In this thesis, we deal with three interrelated problems that decision-makers encounter during the process of arriving at a final decision. Our work addresses decision-making using preference relations. The first problem deals with incomplete reciprocal preference relations, where some of the preference degrees are missing. Ideally, the group members are able to provide preferences for all the alternatives, but sometimes they might not be able to discriminate between some of the alternatives, leading to missing values. Two methods are proposed to handle this problem. The first is based on a system of equations and the second relies on goal programming to estimate the missing information. The former is suitable to complete any incomplete preference relation with at leas