Author
Haiming Liang
Bio: Haiming Liang is an academic researcher from Xidian University. The author has contributed to research in topics: Ranking & Group decision-making. The author has an hindex of 1, co-authored 1 publications receiving 21 citations.
Topics: Ranking, Group decision-making, Preference
Papers
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TL;DR: The minimum deviation consensus ranking model (MDCRM), which seeks to minimize the ordinal information deviation between the original and adjusted preference orderings in the process of reaching consensus, is proposed and the properties of the optimal solution to MDCRM are studied.
24 citations
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TL;DR: The origin and basic research paradigm of the FMMA/C is analyzed, and the feedback mechanism with minimum adjustment or cost has been developed and widely used in various group decision making contexts to improve consensus efficiency.
182 citations
TL;DR: An iterative algorithm is devised to help decision makers reach consensus in MAGDM with multi-granular HFLTSs and the group consensus measure is defined based on the fuzzy envelope of multi- granular H FLTSs.
Abstract: Due to the uncertainty of decision environment and differences of decision makers’ culture and knowledge background, multi-granular HFLTSs are usually elicited by decision makers in a multi-attribute group decision making (MAGDM) problem. In this paper, a novel consensus model is developed for MAGDM based on multi-granular HFLTSs. First, it is defined the group consensus measure based on the fuzzy envelope of multi-granular HFLTSs. Afterwards, an optimization model which aims to minimize the overall adjustment amount of decision makers’ preference is established. Based on the model, an iterative algorithm is devised to help decision makers reach consensus in MAGDM with multi-granular HFLTSs. Numerical results demonstrate the characteristics of the proposed consensus model.
130 citations
TL;DR: A novel method is developed to calculate the weights of decision-makers in LSGDM environments and an independent consensus-reaching model is put forward to address situations where multiple decision-maker modify their opinions in each iteration, and a mixed consensus model is constructed.
46 citations
TL;DR: A model for increasing the consensus level is built that ensures the smallest total adjustment and allows the adjusted proportions of different judgements to be different and a comparison of different GDM methods with heterogeneous preference relations is made.
41 citations
TL;DR: A consensus model for heterogeneous MAGDM with several attribute sets, in which each decision maker can independently choose evaluation attributes, set attribute weights, express evaluation information, and then decision makers can reach an agreement through a consensus reaching process.
Abstract: In most of the consensus models for multi-attribute group decision making (MAGDM), the decision makers are required to provide evaluation information in given expression domains under the same evaluation attributes, which cannot well represent the heterogeneity of evaluation information and the differences of decision makers to meet the realistic requirements. In this work, we propose a consensus model for heterogeneous MAGDM with several attribute sets, in which each decision maker can independently choose evaluation attributes, set attribute weights, express evaluation information, and then decision makers can reach an agreement through a consensus reaching process. The key of the proposed model is to transform the individual heterogeneous evaluation attributes of each decision maker into corresponding two homogeneous evaluation attributes, i.e. the distance from the alternatives to the Positive Ideal Solution (PIS) and the distance from the alternatives to the Negative Ideal Solution (NIS). More specifically, every evaluation attribute of each decision maker is regarded as a small module. Then, the heterogeneous TOPSIS method is used to calculate the separation from NIS and proximity to PIS of alternatives in small modules and aggregate these distances under different attributes of the same alternative using attribute weights for each decision maker; then, consensus process and selection process are implemented via the new homogeneous evaluation attributes of alternatives for decision makers. Two case studies illustrate the effectiveness of the proposed model.
33 citations