المؤلفون: Yu Wei Chang, Chung-Hsing Yeh, Yu Hern Chang

المصدر: Applied Soft Computing. 13:2179-2187

مصطلحات موضوعية: business.industry, Weighted product model, Multiple-criteria decision analysis, Machine learning, computer.software_genre, Defuzzification, Outcome (game theory), Fuzzy logic, Group decision-making, Ranking, Artificial intelligence, business, computer, Software, Selection (genetic algorithm), Mathematics

الوصف: Fuzzy multicriteria decision making (MCDM) has been widely used in ranking a finite number of decision alternatives characterized by fuzzy assessments with respect to multiple criteria. In group decision settings, different fuzzy group MCDM methods often produce inconsistent ranking outcomes for the same problem. To address the ranking inconsistency problem in fuzzy group MCDM, this paper develops a new method selection approach for selecting a fuzzy group MCDM method that produces the most preferred group ranking outcome for a given problem. Based on two group averaging methods, three aggregation procedures and three defuzzification methods, 18 fuzzy group MCDM methods are developed as an illustration to solve the general fuzzy MCDM problem that requires cardinal ranking of the decision alternatives. The approach selects the group ranking outcome of a fuzzy MCDM method which has the highest consistency degree with its corresponding ranking outcomes of individual decision makers. An empirical study on the green bus fuel technology selection problem is used to illustrate how the approach works. The approach is applicable to large-scale group multicriteria decision problems where inconsistent ranking outcomes often exist between different fuzzy MCDM methods.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::93fc095c7eb8d2df4aae0bd507795bd7
https://doi.org/10.1016/j.asoc.2012.12.009

المؤلفون: Soheil Sadi-Nezhad, Kaveh Khalili-Damghani

المصدر: Applied Soft Computing. 13:339-352

مصطلحات موضوعية: Knowledge management, Operations research, business.industry, Computer science, Investment (macroeconomics), Fuzzy logic, Preference, Group decision-making, Ranking, Goal programming, Multiple criteria, Fuzzy number, business, Strategic alliance, Software

الوصف: In this paper, a new hybrid fuzzy multiple criteria group decision making (FMCGDM) approach has been proposed for sustainable project selection. First, a comprehensive framework, including economic, social, and environmental effects of an investment, strategic alliance, organizational readiness, and risk of investment has been proposed for sustainable project selection. As the relative importance of the criteria of the proposed framework are hard to find through several conflictive preferences of a group of Decision Makers (DMs) so, a goal programming (GP) has been supplied to this aim considering multiplicative and fuzzy preference relation. Then, a fuzzy TOPSIS method has been developed to assess the fitness of investment chances. It is based on Preference Ratio (PR), which is known as an efficient ranking method for fuzzy numbers, and a fuzzy distance measurement. The properties of proposed hybrid approach make it robust for modeling real case of uncertain group decision making problems. The FMCGDM has been developed through a linkage between Lingo 11.0, MS-Excel 12.0, and Visual Basic 6.0. The proposed hybrid approach has been applied in a real case study called Iranian financial and credit institute for sustainable project selection.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::32319ea29331c1ff1affd9d019ef4955
https://doi.org/10.1016/j.asoc.2012.07.030

المؤلفون: Mehdi Fasanghari, Samrand Khaleie, Ensi Tavassoli

المصدر: Applied Soft Computing. 12:1741-1754

مصطلحات موضوعية: Mathematical optimization, Fuzzy clustering, Rank (computer programming), Score, computer.software_genre, Group decision-making, Ranking, Factory (object-oriented programming), Data mining, Cluster analysis, computer, Software, Selection (genetic algorithm), Mathematics

الوصف: Supplier selection is a complicated decision-making problem involving multicriteria, alternative and decision makers (DMs). The main purpose of this paper is to demonstrate the use of a clustering-based method to solve a group decision making (GDM) problem and, also to achieve more realistic and homogeneous results. Intuitionistic fuzzy value (IFV) is used to show the decision makers' preferences and IFN clustering method is utilized to cluster around DM's preferences. Intuitionistic fuzzy weighted geometric (IFWG) is applied to aggregate the obtained clusters. Ranking process is used based on the two indices, score function and accuracy function, to rank the alternatives. Lastly, to demonstrate the efficiency of our proposed method, it is implemented to choose suppliers in a car factory. The strength of the propose approach is considering the group agreement on proposed DMs' preferences for giving different effect on their judgment. Besides, encountering the qualitative judgment of DMs using IFV concept with score function and the accuracy function for modeling the DMs' knowledge is the other contribution of this paper.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::11f7a5387628d74524e222eccb2187df
https://doi.org/10.1016/j.asoc.2012.01.017

المؤلفون: Mahdi Zarghami

المصدر: Applied Soft Computing. 11:1067-1073

مصطلحات موضوعية: Soft computing, Ranking, business.industry, Borda count, Quantifier (linguistics), Variance (accounting), Artificial intelligence, Special case, business, Social choice theory, Software, Mathematics, Group decision-making

الوصف: Borda count is a well-known social choice method frequently used for group decision making problems, however, it does not consider the optimistic/pessimistic view of the director, which has a great effect on group decisions. In the present study, the traditional Borda method is extended by using the ordered weighted averaging (OWA) operator to consider the risk-attitudinal characteristics. The new approach, entitled Borda-OWA, solves the group decision making problem in a more intelligent procedure. Borda-OWA is then applied on two real case studies of forest management and projects ranking. The outcomes show that the Borda-OWA operator produces more soft and sensitive results by using the director's risk attitudes, guided by the fuzzy linguistic quantifiers. These results are examined by sensitivity analysis, which shows the significance of selecting the suitable quantifier. It is also shown that the original Borda is a special case of the Borda-OWA approach, indicating only the neutral view for the director. Because of the uncertainty in selecting the quantifier, we have defined a new measure, which considers both the expected value and the variance of the combined goodness measure for each alternative. By using this measure, the Borda-OWA model will give more robust decision to the stakeholders whose optimism degrees are different than that of the group director.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::1332df53956483d92613ea960b90caa5
https://doi.org/10.1016/j.asoc.2010.02.006

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

المؤلفون: Aykut I. Ölçer, C. Tuzcu, Osman Turan

المصدر: Applied Soft Computing. 6:221-243

مصطلحات موضوعية: Mathematical optimization, business.industry, Computer science, Fuzzy set, Multiple-criteria decision analysis, computer.software_genre, Fuzzy logic, Group decision-making, Ranking, Genetic algorithm, Fuzzy number, Data mining, business, computer, Software, Subdivision

الوصف: This paper focuses on developing a new multiple criteria decision-making (MCDM) methodology for subdivision arrangement of Ro-Ro vessels, which integrates the multi-objective optimisation with a fuzzy multi-attributive group decision-making (FMAGDM) technique. The study concentrates on the task of finding and then evaluating (or ranking) the finite number of pareto-optimal design alternatives (PODAs). A genetic algorithm based multi-objective optimisation technique, namely MOGA, is employed for optimisation purpose in terms of chosen design parameters such as damage stability, survivability, and cargo capacity. MOGA is the methodology where the solution space is searched for a set of PODAs, from which experts can express their opinions and choose the best PODA. The subjectiveness and imprecision of the ranking process is modelled as linear trapezoidal fuzzy numbers by means of linguistic terms. An attribute based aggregation technique for homogeneous and heterogeneous groups of experts is employed and used for dealing with the fuzzy opinion aggregation. Finally, a real case study on the subdivision arrangement of a Ro-Ro vessel is conducted to illustrate the effectiveness of the approach.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::79e52f75c5f669b9b1ae8970344e1cff
https://doi.org/10.1016/j.asoc.2005.01.004

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.