Strategic Solutions for Warehouse Optimization: Tackling the Storage Location Assignment Problem
Résumé
This paper addresses the Storage Location Assignment Problem (SLAP) in warehouse management, focusing on minimizing total picking and replenishment costs through two proposed methods. The first approach is a greedy algorithm that prioritizes high-demand items and assigns them to storage locations, optimizing picking costs efficiently but without guaranteeing a global optimum. The second approach uses network flow theory, leveraging the Maximum Flow of Minimum Cost concept via the Hungarian algorithm, to optimize both picking and replenishment costs. Applied to a real dataset, the results show that the Hungarian algorithm outperforms the initial solution, providing a more effective balance between different cost components. This work highlights the potential for further multi-objective optimization to enhance warehouse efficiency.
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