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A novel framework for production planning and class-based storage location assignment: Multi-criteria classification
Mehmet Akif Yerlikaya1, Feyzan Arıkan2
1Department of Industrial Engineering, Bitlis Eren University, Bitlis, 13000, Turkey.
Heliyon
|September 23, 2024
Summary
This study presents a new Mixed-Integer Nonlinear Programming (MINLP) model for the Storage Location Assignment Problem (SLAP). It uses Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to optimize warehouse inventory and reduce costs.
Area of Science:
- Operations Research
- Logistics Management
- Industrial Engineering
Background:
- Efficient warehouse management is critical for optimizing inventory and reducing operational costs.
- The Storage Location Assignment Problem (SLAP) is a key challenge in warehouse operations.
- Existing methods often lack comprehensive consideration of diverse inventory attributes.
Purpose of the Study:
- To develop a novel Mixed-Integer Nonlinear Programming (MINLP) model for the Storage Location Assignment Problem (SLAP).
- To integrate multi-criteria decision-making, specifically the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), into warehouse management strategies.
- To enhance warehouse efficiency by strategically allocating storage locations based on product characteristics and demand.
Main Methods:
- Formulation of a novel Mixed-Integer Nonlinear Programming (MINLP) model for SLAP.
- Application of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate and classify inventory based on physical characteristics and perishability.
- Integration of TOPSIS outcomes as inputs into the mathematical model for storage location assignment.
- Development of a versatile decision support system for adaptable warehouse management scenarios.
Main Results:
- The proposed MINLP model effectively addresses the SLAP by strategically assigning storage locations.
- The integration of TOPSIS allows for a more comprehensive evaluation of storage locations, considering spatial, demand, and physical aspects.
- The decision support system provides practical tools for single or multiple criteria-based decision-making, including the cube-per-order index (COI).
Conclusions:
- The novel MINLP model, enhanced by TOPSIS, significantly improves warehouse management efficiency and cost-effectiveness.
- The approach offers a practical and adaptable solution for complex storage location assignment challenges.
- This research contributes a valuable methodology to the field of logistics and supply chain optimization.
Keywords:
COIClass-based storage location assignmentDecision support system flowProduction planningTOPSISMore Related Videos
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