<![CDATA[In the aviation industry, determining vendors for aircraft materials is an important task that can affect the quality, reliability and safety of aircraft. The selection of the right material for the aircraft is crucial, because it is closely related to the operational sustainability and overall performance of the aircraft. However, determining vendors for aircraft materials often involves a variety of complex criteria and requires an efficient and precise approach. In this study, using the Particle Swarm Optimization (PSO) Algorithm to solve the problem of determining aircraft material vendors. The PSO algorithm has proven effective in a variety of optimization problems and offers a population-based approach inspired by group behavior in nature. By utilizing the PSO algorithm, it can optimize the process of determining vendors for aircraft materials by considering criteria such as quality of delivery and average quality score. The results of the research show that the PSO algorithm is able to find the optimal combination of vendors efficiently, thereby helping stakeholders make more informed and result-oriented decisions. In addition, the results of this study also show that the PSO algorithm itself has a weakness, namely being stuck at a local optimum, having difficulty finding global solutions. Particles moving towards a local optimum may reduce exploration effort to find a better solution globally.]]>
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