A Scientific Decision Framework For Cloud Vendor Prioritization Under Probabilistic Linguistic Term Set Context With Unknown Partial Weight Information
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A Scientific Decision Framework for Cloud Vendor Prioritization under Probabilistic Linguistic Term Set Context with Unknown/Partial Weight Information
With the tremendous growth of Cloud Vendors, Cloud vendor (CV) prioritization is a complex decision-making problem. Previous studies on CV selection use functional and non-functional attributes, but do not have an apt structure for managing uncertainty in preferences. Motivated by this challenge, in this paper, a scientific framework for prioritization of CVs is proposed, which will help organizations to make decisions on service usage. Probabilistic linguistic term set (PLTS) is adopted as a structure for preference information, which manages uncertainty better by allowing partial information ignorance. Decision makers’ (DMs) relative importance is calculated using the programming model, by properly gaining the advantage of the partial knowledge and attributes, the weights are calculated using the extended statistical variance (SV) method. Further, DMs preferences are aggregated using a hybrid operator, and CVs are prioritized, using extended COPRAS method under the PLTS context. Finally, a case study on CV prioritization is provided for validating the scientific framework and the results are compared with other methods for understanding the strength and weakness of the proposal.
Multi-Criteria Decision-Making Techniques for Improvement Sustainability Engineering Processes
Author: Edmundas Kazimieras Zavadskas
language: en
Publisher: MDPI
Release Date: 2020-12-15
The success of any activity and process depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction. That is, the ability to properly define a set of success indicators. The application of the developed new multi-criteria decision-making (MCDM) methods can be eliminated or decreased by decision-makers’ subjectivity, which leads to consistency or symmetry in the weight values of the criteria. In this Special Issue, 40 research papers and one review study co-authored by 137 researchers from 23 different countries explore aspects of multi-criteria modeling and optimization in crisp or uncertain environments. The papers propose new approaches and elaborate case studies in the following areas of application: MCDM optimization in sustainable engineering, environmental sustainability in engineering processes, sustainable multi-criteria production and logistics processes planning, integrated approaches for modeling processes in engineering, new trends in the multi-criteria evaluation of sustainable processes, and multi-criteria decision-making in strategic management based on sustainable criteria.
q-Rung Orthopair Fuzzy Sets
This book collects chapters which discuss interdisciplinary solutions to complex problems by using different approaches in order to save money, time and resources. The book presents the results on the recent advancements in artificial intelligence, computational intelligence, decision-making problems, emerging problems and practical achievements in the broad knowledge management field. q-ROFS is one of the hot topics for all the researchers, industrialists as well as academicians. This book is of interest to professionals and researchers working in the field of decision making and computational intelligence, as well as postgraduate and undergraduate students studying applications of fuzzy sets. The book helps solve different kinds of the decision-making problems such as medical diagnosis, pattern recognition, construction problems and technology selection under the uncertain fuzzy environment. Containing 19 chapters, the book begins by giving a topology of the q-ROFSs and their applications. It then progresses in a logical fashion, dedicating a chapter to each approach, including the generalized information measures for q-ROFSs, implementation of q-ROFSs to medical diagnosis, inventory model, multi-attribute decision-making and approaches to real-life industrial problems such as green campus transportation, social responsibility evaluation pattern and extensions of the q-ROFSs.