Ramping up a heuristic procedure for storage location assignment problem with precedence constraints

Area of Science:

• Operations Research
• Supply Chain Management
• Retail Logistics

Background:

• Increasing competition in retail necessitates supply chain efficiency improvements.
• Optimizing warehouse operations, specifically product allocation, is key to reducing inefficiencies.
• The storage location assignment problem (SLAP) is critical for efficient warehouse management.

Purpose of the Study:

• To propose a novel heuristic approach for the storage location assignment problem (SLAP) in multi-aisle, multi-product warehouses.
• To address SLAP with precedence constraints, considering product similarity, demand, weight, and picker travel distance.
• To offer an effective alternative to traditional density zone methods for product allocation.

Main Methods:

• A two-phase heuristic procedure was developed for product clustering and space assignment.
• The method was tested in a real-world non-perishables warehouse of a Portuguese retail chain.
• The procedure integrated four key criteria: product similarity, demand, weight, and travel distance.

Main Results:

• The new product assignment strategy improved picker travel distance by up to 15%.
• This improvement translates to potential monthly savings of approximately 477 km in travel distance.
• The heuristic effectively handled a large percentage of non-uniform products, a specific challenge in SLAP.

Conclusions:

• The proposed two-phase heuristic offers a more effective solution for SLAP compared to existing density zone methods.
• This approach provides significant operational improvements and cost savings for retail warehouses.
• The study contributes a valuable alternative for academics and practitioners in warehouse optimization.