In consensus-based multiple attribute group decision making (MAGDM) problems, it is frequent that some experts exhibit non-cooperative behaviors owing to the different areas to which they may belong ...and the different (sometimes conflicting) interests they might present. This may adversely affect the overall efficiency of the consensus reaching process, especially when some uncooperative behaviors by experts arise. To this end, this paper develops a novel consensus framework based on social network analysis (SNA) to deal with non-cooperative behaviors. In the proposed SNA-based consensus framework, a trust propagation and aggregation mechanism to yield experts’ weights from the social trust network is presented, and the obtained weights of experts are then integrated into the consensus-based MAGDM framework. Meanwhile, a non-cooperative behavior analysis module is designed to analyze the behaviors of experts. Based on the results of such analysis during the consensus process, each expert can express and modify the trust values pertaining other experts in the social trust network. As a result, both the social trust network and the weights of experts derived from it are dynamically updated in parallel. A simulation and comparison study is presented to demonstrate the efficiency of the SNA-based consensus framework for coping with non-cooperative behaviors.
•A review of the consensus processes in social network group decision making is presented.•Two approaches are identified: consensus based on trust relationships and based on opinion ...evolution.•Challenges and research future fields are presented.
In social network group decision making (SNGDM), the consensus reaching process (CRP) is used to help decision makers with social relationships reach consensus. Many CRP studies have been conducted in SNGDM until now. This paper provides a review of CRPs in SNGDM, and as a result it classifies them into two paradigms: (i) the CRP paradigm based on trust relationships, and (ii) the CRP paradigm based on opinion evolution. Furthermore, identified research challenges are put forward to advance this area of research.
In real-world Multiple Attribute Decision Making (MADM) problem, the attribute weights information may be unknown or partially known. Several approaches have been suggested to address this kind of ...incomplete MADM problem. However, these approaches depend on the determination of attribute weights, and setting different attribute weight vectors may result in different ranking positions of alternatives. To deal with this issue, this paper develops a novel MADM approach: the ranking range based MADM approach. In the novel MADM approach, the minimum and maximum ranking positions of every alternative are generated using several optimization models, and the average ranking position of every alternative is produced applying the Monte Carlo simulation method. Then, the minimum, maximum and average ranking positions of the alternative are integrated into a new ranking position of the alternative. This novel approach is capable of dealing with venture investment evaluation problems. However, in the venture investment evaluation process, decision makers will present different risk attitudes. To deal with this issue, two ranking range based MADM approaches with risk attitudes are further designed. A case study and a simulation experiment are presented to show the validity of the proposal.
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•We propose a novel consensus framework from two aspects: preferences-modifying and weights-updating.•We propose three optimization-based consensus models to support the novel ...consensus framework.•The novel consensus framework needs less adjustment amounts (in the sense of Manhattan distance).
This study put forwards a novel consensus framework to manage the consensus and weights (i.e., weights of the experts and attributes) in iterative multiple-attribute group decision making (MAGDM) problem. In this consensus framework, an optimization-based consensus model is devised to support the process of preferences-modifying, which seeks to minimize the adjustment amounts (in the sense of Manhattan distance) between the original and adjusted preferences. Then, the other two optimization-based consensus models are constructed to support the weights-updating, in which the consensus level among experts can be further improved. A numerical example is provided to show the application of the proposed consensus framework, and a detailed comparison analysis is presented to verify the effectiveness of the proposed consensus framework.
In this paper, we investigated the vertical distribution characteristics of surface soil moisture based on ISMN (International Soil Moisture Network) multilayer in situ data (5, 10, and 20 cm; 2, 4, ...and 8 in) and performed comparisons between the in situ data and four microwave satellite remote sensing products (SMOS L2, SMOS-IC, SMAP L2, and SMAP L4). The results showed that the mean soil moisture difference between layers can be −0.042~−0.024 (for the centimeter group)/−0.067~−0.044 (for the inch group) m3/m3 in negative terms and 0.020~0.028 (for the centimeter group)/0.036~0.040 (for the inch group) m3/m3 in positive terms. The surface soil moisture was found to have very significant stratification characteristics, and the interlayer difference was close to or beyond the SMOS and SMAP 0.04 m3/m3 nominal retrieval accuracy. Comparisons revealed that the satellite retrievals had a higher correlation with the field measurements of 5 cm/2 in, and SMAP L4 had the smallest difference with the in situ data. The mean difference caused by using 10 cm/4 in and 20 cm/8 in in situ data instead of the 5 cm/2 in data could be about −0.019~−0.018/−0.18~−0.015 m3/m3 and −0.026~−0.023/−0.043~−0.039 m3/m3, respectively, meaning that there would be a potential depth mismatch in the data validation.
Opinion dynamics is an opinion evolution process of a group of agents, where the final opinion distribution tends to three stable states: consensus, polarization, and fragmentation. At present, the ...opinion dynamics models have been extensively studied in differrent fields. This paper provides a review of opinion dynamics in finance and business, such as, finance, marketing, e-commerce, politics, and group decision making. Furthermore, identified research challenges have been proposed to promote the future research of this topic.
With the development of Internet technologies, the shipping industry has also entered the Industry 4.0 era, which is the era of using information technology to promote industrial change. Group ...decision making (GDM), as one of the key methods in decision science, can be used to obtain optimal solutions by aggregating the opinions of experts on several alternatives, and it has been applied to many fields to optimize the decision-making process. This paper provides an overview and analysis of the specific applications of GDM methods in Shipping Industry 4.0, and discusses future developments and research directions. First, the existing relevant literature is analyzed using bibliometrics. Then, the general procedure of GDM is investigated: opinion/preference representation, consensus measure, feedback mechanism, and the selection of alternatives. Next, the specific applications of GDM methods in Shipping Industry 4.0 are summarized. Lastly, possible future directions are discussed to advance this area of research.
Melanin-inspired polymers have been widely used in biomedical applications due to their promising biocompatibility and antioxidant capacity. Although several works focusing on the eumelanin-like ...biomaterials such as polydopamine nanoparticles (PDA NPs) have been well documented, their free radical scavenging capability usually needed to be tailored and improved for some cases of antioxidative therapy. Herein, a kind of fungal melanin-like, poly-(1,8-dihydroxynaphthalene) nanoparticles (PDHN NPs) with uniform and controllable sizes have been synthesized via a facile ammonium persulfate (APS)-mediated oxidative radical polymerization. These resulting PDHN NPs exhibited excellent stability in water and many organic solutions, which could be used for long-term storage and various biological applications. Moreover, the as-prepared PDHN NPs and PDHN NPs incorporated hydrogels both showed excellent free radical scavenging activity in vitro and in vivo, resulting to the accelerated wound healing behaviors. This study would provide a simple strategy to develop new kinds of melanin-like materials with high stability and excellent antioxidative property for biomedical applications.
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The 360 degree feedback evaluation method is a multidimensional, comprehensive assessment method. Evaluators may hesitate among multiple evaluation values and be simultaneously constrained by the ...biases and cognitive errors of the evaluators, evaluation results are prone to unfairness and conflicts. To overcome these issues, this paper proposes a consensus-based 360 degree feedback evaluation method with linguistic distribution assessments. Firstly, evaluators provide evaluation information in the form of linguistic distribution. Secondly, utilizing an enhanced ordered weighted averaging (OWA) operator, the model aggregates multi-source evaluation information to handle biased evaluation information effectively. Subsequently, a consensus-reaching process is established to coordinate conflicting viewpoints among the evaluators, and a feedback adjustment mechanism is designed to guide evaluators in refining their evaluation information, facilitating the attainment of a unanimous evaluation outcome. Finally, the improved 360 degree feedback evaluation method was applied to the performance evaluation of the project leaders in company J, thereby validating the effectiveness and rationality of the method.
Because of the von Neumann bottleneck, neuromorphic networks aimed at in-memory computing, such as brains, are extensively studied. As artificial synapses are essential in neuromorphic networks, a ...photonic synapse based on slot-ridge waveguides with nonvolatile phase-change materials (PCMs) was proposed and demonstrated in an SOI platform with standard complementary metal-oxide-semiconductor (CMOS) process for a larger weight dynamic range. The change of the optical transmission spectrum of our photonic synapses was about 3.5dB higher than that of primitive synapses, which meant large weight dynamic range and more weight values. A 90.7% recognition accuracy based on our photonic synapses, which was 2.6% higher than that of primitive synapses, was realized for the MNIST handwritten digits recognition task performed by a three-layer perceptron. Besides, because of the nonvolatile nature of PCMs, the weights achieved by our photonic synapses can be stored in situ ensuring a lower consumption in in-memory computing. This framework can potentially achieve a more efficient in-memory computing neuromorphic network in silicon photonics.
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