Browsing by Author "Wang, Fang"

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    Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks.
    (IEEE, 2010) Yang, Shengxiang; Cheng, Hui; Wang, Fang
    In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.
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    Graph Model for Conflict Resolution With Internal Consensus Reaching and External Game
    (IEEE, 2024-07-18) Zhang, Hengjie; Wang, Fang; Dong, Yucheng; Chiclana, Francisco; Herrera-Viedma, Enrique
    The graph model is devoted to game conflicts arising from incongruent pursued objectives among conflicting parties. Considering that each conflicting party is composed of multiple individuals, preference conflicts stemming from differing cognitive levels and knowledge backgrounds exist among internal individuals. This scenario simultaneously involving game conflicts and preference conflicts is termed dual conflict decision-making problem. Tailored to effectively address this problem, this study proposes an enhanced graph model that incorporates internal consensus and external stability. The best–worst method, incorporating comparative linguistic expressions, is devised to effectively elicit individual preferences over game states. To mitigate preference conflicts inherent to internal individuals within conflicting party concerning game states, a consensus reaching model minimizing preference information loss is introduced. By this way, collective preferences are obtained. Based on these, the concept of “game consensus” is proposed to manage the game conflicts and the diverse behaviors exhibited by conflicting party. Finally, a case study regarding price conflict within a dual-channel supply chain, accompanied by a comparative analysis, is presented to validate the effectiveness of the proposal. Compared to existing graph model, the proposal effectively grapples with consensus issues and heterogeneous behaviors within conflicting parties, making it more valuable in practice.
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    Social trust-driven consensus reaching model with a minimum adjustment feedback mechanism considering assessments-modifications willingness
    (IEEE, 2021-04-14) Zhang, Hengjie; Wang, Fang; Dong, Yucheng; Chiclana, Francisco; Herrera-Viedma, Enrique
    Social network group decision-making (SNGDM) has emerged as a new decision tool to effectively model the social trust relationships among decision makers. The impact of the social trust relationships on assessments-modifications in the consensus reaching in the SNGDM is seldom considered. This study aims at addressing this issue. The main starting point is the assumption that a decision maker will not be willing to accept the assessments-modifications suggestions that significantly differ from his/her trusted decision makers’ assessments in a social trust network. Thus, this study proposes a social trust–driven minimum adjustments consensus model (STDMACM) for SNGDM. Simultaneously, a social trust–driven consensus maximum optimization model (STDCMOM) is proposed for maximizing the consensus level among decision makers under the above assumption. Based on both STDCMOM and STDMACM, an interactive consensus reaching process is presented, in which the assessments-modifications suggestions generated from the STDMACM are used, when the maximum consensus level obtained from STDCMOM is acceptable, as the references for guiding the consensus reaching; otherwise, assessments modifications suggestions are generated from the designed STDCMOM. The validity of the social trust-driven consensus reaching process with respect to its consensus convergence rate and consensus success ratio is verified with a simulation and comparison analysis.
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    Supporting consensus reaching on prioritizing failure modes in reliability management: The role of social trust-driven rating-modifications willingness
    (IEEE, 2023-11-14) Zhang, Hengjie; Zhang, Wenwen; Wang, Fang; Chen, Xia; Dong, Yucheng; Chiclana, Francisco
    Failure modes and effect analysis (FMEA) is a promising reliability management approach widely used to prioritize the failure modes. Different backgrounds and levels of knowledge of FMEA participants may lead to substantial variation between their risk-ratings, making the implementation of a consensus mechanism within FMEA to assist FMEA participants in reaching acceptable collective risk-ratings worthwhile. Since social trust has an influence on individual's willingness to change risk-ratings, this study discusses the role of social trust-driven rating-modifications willingness in prioritizing failure modes during the consensus reaching process. FMEA participants' rejection of rating-modifications suggestions significantly different to their trusted FMEA participants' risk-ratings is formulated as the basis assumption. Based on this assumption, a two-stage social trust-driven consensus model is proposed to assist FMEA participants with linguistic distribution assessment in reaching consensus willingly. The proposed framework implements a social trust-driven consensus model with minimum number of rating-modifications in its first stage, and a social trust-driven consensus model with minimum distance of rating-modifications in its second stage. A case study, related to the reliability management of automatic transmission of new energy vehicles, and a simulation analysis are presented and analyzed to validate the proposed FMEA approach.