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Statistical method confirms rankings of design evaluation criteria in the automobile industry, suggesting AHP enhances decision-making.
When selecting a material flow layout, the layout's design is assessed using various Cr, including distance, throughput time, shape ratio, adjacency, and safety. To rank these Cr, multiple algorithms are employed. Fuzzy AHP, for instance, is utilized to rank the Cr and determine their respective weights. Within the Analytic Hierarchy Process (AHP), a ratio scale, represented as ( , …, ), establishes the priorities of evaluation Cr { , …, } for decision-making. The ratio quantifies the preference of Cr over . For group decision-making, experts provide subjective estimates of , which form entries in a pairwise comparison matrix. The AHP algorithm then calculates the weights of these Cr, which in turn establishes their ranking. This article applies a statistical method to validate the ranking of design evaluation Cr. This approach involves hypothesis testing to confirm the AHP algorithm's ranking, relying on comparative ratings from automobile industry experts.
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Gautam et al. (2025) studied this question.
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