Druck auf Anfrage Neuware - Printed after ordering - This monograph discusses the theoretical and practical development of multicriteria decision making (MCDM). The main purpose of MCDM is the construction of systematized strategies for the 'optimisation' of feasible options, as well as the justification of why some alternatives can be declared 'optimal'. However, at time, we must make decisions in an uncertain environment and such inconvenience gives rise to a much more elaborate scenario. This book highlights models where this lack of certainty can be flexibly fitted in and goes on to explore valuable strategies for making decisions under a multiplicity of criteria.Methods discussed includebipolar fuzzy TOPSIS method, bipolar fuzzy ELECTRE-I method, bipolar fuzzy ELECTRE-II method, bipolar fuzzy VIKOR method, bipolar fuzzy PROMETHEE method, and two-tuple linguistic bipolar fuzzy Heronian meanoperators.This book is a valuable resource for researchers, computer scientists, and social scientists alike. Bestandsnummer des Verk�ufers 9789819905713

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Titel: Multi-criteria Decision Making Methods with ...

Verlag: Springer Nature Singapore, Springer Nature Singapore

Erscheinungsdatum: 2024

Einband: Taschenbuch

Zustand: Neu

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This monograph discusses the theoretical and practical development of multicriteria decision making (MCDM). The main purpose of MCDM is the construction of systematized strategies for the "optimisation" of feasible options, as well as the justification of why some alternatives can be declared "optimal". However, at time, we must make decisions in an uncertain environment and such inconvenience gives rise to a much more elaborate scenario. This book highlights models where this lack of certainty can be flexibly fitted in and goes on to explore valuable strategies for making decisions under a multiplicity of criteria. Methods discussed include bipolar fuzzy TOPSIS method, bipolar fuzzy ELECTRE-I method, bipolar fuzzy ELECTRE-II method, bipolar fuzzy VIKOR method, bipolar fuzzy PROMETHEE method, and two-tuple linguistic bipolar fuzzy Heronian mean operators. This book is a valuable resource for researchers, computer scientists, and social scientists alike.

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MUHAMMAD AKRAM is Professor at the Department of Mathematics, University of the Punjab, Lahore, Pakistan. He earned his Ph.D. in fuzzy mathematics from the Government College University, Lahore, Pakistan. His research interests include numerical algorithms, fuzzy graphs, fuzzy algebras, and fuzzy decision support systems. He has published 10 monographs and 485 research articles in international peer-reviewed journals. According to reports from Stanford University for years 2020, 2021 and 2022, Dr. Akram is ranked in the top 2% of scientists for years 2020, 2021 and 2022 in the world in artificial intelligence and image processing. He has been on the editorial of 15 international academic journals and reviewer/referee for 155 international journals, including Mathematical Reviews (USA) and Zentralblatt MATH (Germany). Under his supervision, 17 Ph.D. students have completed their research and he is currently guiding five more towards the same.

SHUMAIZA is a research scholar at the University of Punjab, Lahore, Pakistan, from where she also has earned her M.Phil. degree in Mathematics. She has won the HEC indigenous scholarship for her Ph.D. program and has published 15 research articles in renowned international peer-reviewed journals. Her area of research is fuzzy systems.

JOS� CARLOS R. ALCANTUD is Full Professor at the Department of Economics and Economic History, University of Salamanca, Spain, since 2010, and has been heading the BORDA Research Unit since 2015. He received his Ph.D. in Mathematics in 1996 from the University of Santiago de Compostela, Spain and M.Sc. in Mathematics in 1991 from the University of Valencia, Spain. His research interests include social choice theory, mathematical economics, and fuzzy theory and decision support systems. He has published over 200 papers on these topics and has supervised 3Ph.D. students on their research.

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