Abstract:
The selection of a Warehouse Management System (WMS) is essential for optimising logistics and inventory processes, especially in light of the rapid development within the supply chain sphere. This project investigates how the Analytical Hierarchy Process (AHP) can support this selection. The AHP is a decision-making tool that helps to identify the most appropriate alternative by independently analysing provided criteria and sub-criteria. Given the significant role of WMS in Industry 4.0, where data must be processed immediately, the challenge of making informed decisions is highly relevant.
The research begins with a comprehensive investigation of prior studies and methodologies on the Warehouse Management System and Analytical Hierarchy Process, highlighting the limitations of the complex structure. One of the main advantages of AHP is the ability to break down a decision-making process into more manageable sub-parts. The method provides an ability to make an objective choice of WMS based on three main criteria: technical, administrative and cost value, each was divided into 3 sub- criteria. Each has been weighted according to its relative importance and overall the WMS has been evaluated based on weighted data. The results prove that AHP provides transparent and justified results and a well-observed decision-making process by using both quantitative and qualitative data.
The study also highlights the possible challenges, such as the sensitivity of data provided and the complexity of weighting the criteria, that lead to possible cooperation of AHP with other Milti-Criteria Decision Analysis and advanced technologies like Artificial Intelligence to improve the decision-making process and gain more credible results.
Eventually, this study contributes to the field of supply chain management by providing a detailed framework of how AHP can be used in choosing WMS, advising a detailed explanation to any company and providing a foundation for future research, which can improve and extend the application of AHP in
logistics and beyond it.
