12 research outputs found
Consistency and Consensus Driven for Hesitant Fuzzy Linguistic Decision Making with Pairwise Comparisons
Hesitant fuzzy linguistic preference relation (HFLPR) is of interest because
it provides an efficient way for opinion expression under uncertainty. For
enhancing the theory of decision making with HFLPR, the paper introduces an
algorithm for group decision making with HFLPRs based on the acceptable
consistency and consensus measurements, which involves (1) defining a hesitant
fuzzy linguistic geometric consistency index (HFLGCI) and proposing a procedure
for consistency checking and inconsistency improving for HFLPR; (2) measuring
the group consensus based on the similarity between the original individual
HFLPRs and the overall perfect HFLPR, then establishing a procedure for
consensus ensuring including the determination of decision-makers weights. The
convergence and monotonicity of the proposed two procedures have been proved.
Some experiments are furtherly performed to investigate the critical values of
the defined HFLGCI, and comparative analyses are conducted to show the
effectiveness of the proposed algorithm. A case concerning the performance
evaluation of venture capital guiding funds is given to illustrate the
availability of the proposed algorithm. As an application of our work, an
online decision-making portal is finally provided for decision-makers to
utilize the proposed algorithms to solve decision-making problems.Comment: Pulished by Expert Systems with Applications (ISSN: 0957-4174
Heterogeneous group decision making with thermodynamical parameters
There often exist different types of information due to the subjective
and objective criteria in practical decision-making problems,
thus it is necessary to develop some efficient frameworks to
deal with the decision-making problems with heterogeneous
information. The paper proposes a framework for group decisionmaking
problems with heterogeneous information with thermodynamical
parameters consisting of three parts to achieving this
goal. The first part builds the rectifications of criteria weights
according to decision makers’ confidence in evaluations. The
second part adopts thermodynamical parameters to measure the
numerical values and the data distribution of heterogeneous
information to characterize the heterogeneous information fully.
The last part applies the TODIM (an acronym in Portuguese for
Interactive and Multicriteria Decision Making) to aggregate the
decision-making results based on the characterized heterogeneous
information without transforming it into a unified form. By
depicting decision makers’ different sensitive attitudes towards
uncertainty by several mathematical expressions, experiments are
performed to assess the sensitive attitudes’ impacts on decisionmaking
results with the proposed framework. Finally, a case study
on the selection of a green supplier under the low-carbon economy
is provided to illustrate the flexibility and feasibility of the
proposed framework
An Inverse Prospect Theory Based-Approach for Linear Ordinal Ranking Aggregation with Its Application in Site Selection of Electric Vehicle Charging Station
Considering that it is difficult for experts to provide precise preference values for the site selection of electric vehicle charging station in risky environment, this paper develops an approach for linear ordinal ranking aggregation to validly improve the efficiency and accuracy of electric vehicle charging station site selection. At first, the inverse value function of prospect theory is applied to reduce the impact of risk. Then, through combining with the concept of information energy, the experts' weights can be derived. Besides, a consistency constraint is added to the individual ranking-based alternatives' weights deriving model, which can guarantee the consistency degree at an acceptable level. Additionally, a consensus and standard deviation-based model is established to aggregate the alternatives' weights. Finally, a numerical case about the electric vehicle charging station site selection is presented to show the usage of the approach, meanwhile, comparative analysis and sensitivity analysis are also conducted which show the robustness and practicability of the approach
Green Logistic Provider Selection with a Hesitant Fuzzy Linguistic Thermodynamic Method Integrating Cumulative Prospect Theory and PROMETHEE
In the process of evaluating the green levels of cold-chain logistics providers, experts may
hesitate between several linguistic terms rather than give precise values over the alternatives. Due to the
potential profit and risk of business decisions, decision-making information is often based on experts’
expectations of programs and is expressed as hesitant fuzzy linguistic terms. The consistency of evaluation
information of an alternative can reflect the clarity of the alternative in the mind of experts and its own
controversy. This paper proposes a method to use the value transfer function in the cumulative prospect
theory to convert the original hesitant fuzzy linguistic terms into evaluation information based on
reference points. We also introduce the parameters related to the disorder of the systemin the hesitant
fuzzy thermodynamic method to describe the quantity and quality characteristics of the alternatives.
In these kinds of multi-criteria decision-making problems, the weights of criteria are of great importance
for decision-making results. Considering the conflicting cases among criteria, the weights were obtained
by utilizing the PROMETHEE method. An illustrative example concerning green logistics provider
selection was operated to show the practicability of the proposed method.The work was supported in part by the National Natural Science Foundation of China (Nos.
71501135, 71771156, and 71771153), the Scientific Research Foundation for Excellent Young Scholars at Sichuan
University (No. 2016SCU04A23), and the Scientific Research Foundation for Scholars at Sichuan University (No.
YJ201535)
Therapeutic Schedule Evaluation for Brain-Metastasized Non-Small Cell Lung Cancer with A Probabilistic Linguistic ELECTRE II Method
With the rapid development of modern medicine, therapeutic schedules of brain-metastasized non-small cell lung cancer (NSCLC) are expanding. To assist a patient who suffers from brain-metastasized NSCLC to select the most suitable therapeutic schedule, firstly, we establish an indicator system for evaluating the therapeutic schedules; then, we propose a probabilistic linguistic ELECTRE II method to handle the corresponding evaluation problem for the following reasons: (1) probabilistic linguistic information is effective to depict the uncertainty of the therapeutic process and the fuzziness of an expert’s cognition; (2) the ELECTRE II method can deal with evaluation indicators that do not meet a fully compensatory relationship. Simulation tests on the parameters in the proposed method are provided to discuss their impacts on the final rankings. Furthermore, we apply the proposed method to help a patient with brain-metastasized NSCLC at the Sichuan Cancer Hospital and Institute to choose the optimal therapeutic schedule, and we present some sensitive analyses and comparative analyses to demonstrate the stability and applicability of the proposed method
Consistency and consensus driven for hesitant fuzzy linguistic decision making with pairwise comparisons
Hesitant fuzzy linguistic preference relation (HFLPR) is of interest because it provides an efficient way for opinion expression under uncertainty. For enhancing the theory of group decision making (GDM) with HFLPR, the paper introduces a method for addressing the GDM based on consistency and consensus measurements, which involves (1) defining a hesitant fuzzy linguistic geometric consistency index (HFLGCI) and proposing an algorithm for consistency checking and inconsistency improving for HFLPR; (2) proposing a worst consensus index based on the minimum similarity measure between each individual HFLPR and the overall perfect HFLPR in order to build a consensus reaching algorithm based on the acceptable HLFPRs. The convergence and monotonicity of the proposed two procedures is proved. Experiments are performed to investigate the critical values of the defined HFLGCI, and comparative analyses are conducted to show the effectiveness of the proposed method. A case concerning the performance evaluation of venture capital guiding funds is given to illustrate the applicability of the proposed method. As an application of our work, an online decision-making portal is finally provided for decision makers to utilize the proposed method to solve GDM with HFLPRs