Optimizing Fuzzy Multi-Attribute Group Decision Making with Particle Swarm Optimization and Triangular Fuzzy Grey Relational Analysis
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Abstract
This paper introduces a method for group decision-making using particle swarm optimization to address the fuzzy multi-attribute group decision-making (FMGDM) problem, where attribute values are expressed as linguistic variables. Within a predefined linguistic evaluation set, the particle swarm optimization algorithm adjusts the central value points of the associated triangular fuzzy numbers for the linguistic variables, assuming a uniform distribution, to achieve a consistent individual decision matrix. Subsequently, the gray correlation analysis method, which is also based on triangular fuzzy numbers, is employed to rank the fault modes of the A-frame and the boom group in the primary structural system of the LIUHUA10-1CEP crane.
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