Information Sciences: an International Journal
An approach to solve group-decision-making problems with ordinal interval numbers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A mobile decision support system for dynamic group decision-making problems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Modelling group decision making problems in changeable conditions
MDAI'10 Proceedings of the 7th international conference on Modeling decisions for artificial intelligence
Consistency of interval fuzzy preference relations in group decision making
Applied Soft Computing
Modelling heterogeneity among experts in multi-criteria group decision making problems
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
Membership maximization prioritization methods for fuzzy analytic hierarchy process
Fuzzy Optimization and Decision Making
Hesitant fuzzy entropy and cross-entropy and their use in multiattribute decision-making
International Journal of Intelligent Systems
Qualitative preference-based service selection for multiple agents
Web Intelligence and Agent Systems
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Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.