Objective Weights Based on Ordered Fuzzy Numbers for Fuzzy Multiple Criteria Decision-Making Methods

Kacprzak, Dariusz

doi:10.3390/e19070373

Cited by 29 publications

(26 citation statements)

References 24 publications

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“…Rather, the weights of the criteria were developed using the entropy method. The entropy method makes it possible to estimate the importance of analyzed criteria describing the considered solution options based on each of their value discrepancies [Lotfi, Fallahnejad, 2010;Kacprzak, 2017].…”

Section: U7mentioning

confidence: 99%

Technology Selection Using the TOPSIS Method

Halicka¹

2020

Foresight and STI Governance

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nnovative technologies are increasingly determining the competitive advantage of enterprises. They also form the basis for modern manufacturing processes, enabling them to meet the needs of society. Awareness of the need for technological development has become widespread, which has been confirmed by international and national programs, scientific and research activities, as well as emerging institutions. Considering the increasing demand for innovative technologies and a developed market, it appears important to use specific methods and tools for the effective analysis and selection of technologies. This paper presents a proposal to use multi-attribute decision-making methods during technology assessment and selection. The proposed concept combines an S-lifecycle analysis (S-LCA), which determines the performance of a technology, the method of Technology Readiness Levels (TRL), which examines the technological maturity, and the TOPSIS method, which allows for developing a technology ranking. To verify this approach, the example of a ranking and selection of the best road technology in Poland is presented, considering the proposed set of criteria and sub-criteria. In the assessment, the criteria for innovation, competitiveness, and usefulness of this technology were used in addition to S-LSA and TRL methods.

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Section: U7mentioning

confidence: 99%

Technology Selection Using the TOPSIS Method

Halicka¹

2020

Foresight and STI Governance

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“…The next step was to determine the criterion weight vector (Table 9). For this purpose, the entropy method was used [Kacprzak, 2017;Rudnik, Kacprzak, 2017]: E = (e 1 , e 2 , ... e n ),…”

Section: х Mnmentioning

confidence: 99%

Untitled

2020

Foresight and STI Governance

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is an international interdisciplinary peer-reviewed openaccess journal. It publishes original research articles, offering new theoretical insights and practice-oriented knowledge in important areas of strategic planning and the creation of science, technology, and innovation (STI) policy, and it examines possible and alternative futures in all human endeavors in order to make such insights available to the right person at the right time to ensure the right decision. The journal acts as a scientific forum, contributing to the interaction between researchers, policy makers, and other actors involved in innovation processes. It encompasses all facets of STI policy and the creation of technological, managerial, product, and social innovations. Foresight and STI Governance welcomes works from scholars based in all parts of the world. Topics covered include: • Foresight methodologies and best practices; • Long-term socioeconomic priorities for strategic planning and policy making; • Innovative strategies at the national, regional, sectoral, and corporate levels; • The development of National Innovation Systems; • The exploration of the innovation lifecycle from idea to market; • Technological trends, breakthroughs, and grand challenges; • Technological change and its implications for economy, policy-making, and society; • Corporate innovation management; • Human capital in STI; and many others. The target audience of the journal comprises research scholars, university professors, postgraduates, policy-makers, business people, the expert community, undergraduates, and others who are interested in S&T and innovation analyses, foresight studies, and policy issues.

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“…Entropy measures are useful in computing weights of the criteria, and had been used widely in MCGDM problems [23]. Shannon entropy method constitutes one of the techniques to determine the weight of the criteria when it becomes difficult to be provided by the decision-maker [24]. Through the computation of information entropy of a proposed parameter, its weight is determined according to its relative degree of change that impact on equipment, index with larger degree of relative change as larger weight.…”

Section: The Determination Of the Objective Weights Based On Entropy mentioning

confidence: 99%

Probabilistic Linguistic Aggregation Operators Based on Einstein t-Norm and t-Conorm and Their Application in Multi-Criteria Group Decision Making

Agbodah

Darko

2019

Symmetry

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One of the major problems of varied knowledge-based systems has to do with aggregation and fusion. Pang’s probabilistic linguistic term sets denotes aggregation of fuzzy information and it has attracted tremendous interest from researchers recently. The purpose of this article is to deal investigating methods of information aggregation under the probabilistic linguistic environment. In this situation we defined certain Einstein operational laws on probabilistic linguistic term elements (PLTESs) based on Einstein product and Einstein sum. Consequently, we develop some probabilistic linguistic aggregation operators, notably the probabilistic linguistic Einstein average (PLEA) operators, probabilistic linguistic Einstein geometric (PLEG) operators, weighted probabilistic linguistic Einstein average (WPLEA) operators, weighted probabilistic linguistic Einstein geometric (WPLEG) operators. These operators extend the weighted averaging operator and the weighted geometric operator for the purpose of aggregating probabilistic linguistic terms values respectively. Einstein t-norm and Einstein t-conorm constitute effective aggregation tools and they allow input arguments to reinforce each other downwardly and upwardly respectively. We then generate various properties of these operators. With the aid of the WPLEA and WPLEG, we originate the approaches for the application of multiple attribute group decision making (MAGDM) with the probabilistic linguistic term sets (PLTSs). Lastly, we apply an illustrative example to elucidate our proposed methods and also validate their potentials.

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Objective Weights Based on Ordered Fuzzy Numbers for Fuzzy Multiple Criteria Decision-Making Methods

Cited by 29 publications

References 24 publications

Technology Selection Using the TOPSIS Method

Technology Selection Using the TOPSIS Method

Untitled

Probabilistic Linguistic Aggregation Operators Based on Einstein t-Norm and t-Conorm and Their Application in Multi-Criteria Group Decision Making

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