Background: Logistics operations are integral to manufacturing systems, particularly in the transportation processes that occur not only between facilities and stakeholders but also between warehouses and workstations within a facility. The design of functional areas and allocating goods to appropriate zones within the warehouse management system (WMS) are critical activities that substantially influence the efficiency of manufacturing logistics operations. Methods: This study develops a mixed-integer programming (MIP) model to optimize material flow and product routing in manufacturing. The model identifies efficient pathways, assigns products to routes, and determines the required material-handling equipment. It is implemented in Python (3.11.5) using the Pyomo (6.7.3) package and the CBC solver (2.10.11), with sensitivity analysis performed on constraints and decision variables to evaluate robustness. Results: The findings indicate that Material Flow 3 and Material-Handling Equipment 1 represent the optimal configurations for managing the majority of goods within the manufacturing system. Conclusions: The proposed mathematical model supports the decision-making process by enabling adjustments to the proportions of functional areas within the manufacturing logistics system, ensuring operational efficiency and flexibility in response to changing demands. Furthermore, the study offers managerial insights and suggests directions for future research.
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