DOI: 10.11648/j.ijem.20261001.12 ISSN: 2640-1568

Development of Super-Fast Decision Support System for Optimum Packaging Material Selection

Abdullah Abdulkareem, Basil Akinnuli, Emmanuel Olutomilola
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This study developed a rapid Decision Support System (DSS) to improve the efficiency, reliability, accuracy, and consistency of packaging material selection through the automation of the Analytic Hierarchy Process (AHP). Traditional AHP-based selection methods are often time-consuming and computationally demanding, particularly when several criteria and alternatives must be evaluated. To address this limitation, this study adopted a systematic methodology in which the AHP technique was integrated into a Python-based application with a graphical user interface (GUI). Expert judgments were collected through pairwise comparisons and processed within the system to generate automated weight calculations, consistency evaluations, global rankings of alternatives, and sensitivity analysis. The results showed that plastic had the highest global priority score of 0.4202, making it the most preferred packaging material in the decision framework. This was followed by paperboard (0.2315), glass (0.2003), and metal (0.1481). The sensitivity analysis further showed that the ranking remained stable under small changes of 0 to 20% in expert judgments, indicating that the outcomes were reliable and robust. The developed DSS reduced decision-making time by an average of 21.29% compared with a conventional AHP tool. In addition, the system provides automated computations, downloadable graphical outputs, and real-time sensitivity analysis, making it a practical, efficient, and user-friendly tool for selecting packaging materials.

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