Enhancing inventory optimization and management for automotive repair shops

Inventory management is pivotal for automotive repair shops, yet traditional approaches often neglect the intricate relationship between suppliers and repair shops. This study addresses these challenges by proposing an advanced inventory optimization model that better captures real-world purchasing...

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Hauptverfasser: Georgiev, Ivan, Grozev, Dimitar, Beloev, Ivan, Milchev, Mihail, Gladkova, Viktoria
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Inventory management is pivotal for automotive repair shops, yet traditional approaches often neglect the intricate relationship between suppliers and repair shops. This study addresses these challenges by proposing an advanced inventory optimization model that better captures real-world purchasing dynamics. This research aims to refine the existing inventory optimization model by introducing more accurate constraints based on supplier dynamics. The goal is to create a comprehensive framework that better aligns with the complexities of inventory management in the automotive repair industry. The proposed model improves upon traditional methods by incorporating factors such as minimum and maximum purchasing quantities set by suppliers, along with realistic purchase scenarios and changing prices. Binary variables representing whether purchases are made from specific suppliers in given periods enhance the model’s realism. Application of the enhanced model to a numerical example involving the procurement of timing belts for a medium-sized car repair shop demonstrates its effectiveness. Compared to the traditional model, the enhanced model yields a significant cost reduction of over BGN 2500 for a one-year planning period. This study presents an enriched inventory optimization model tailored to the intricacies of the automotive repair industry. By accounting for realistic purchasing constraints and supplier dynamics, the model offers an effective solution for repair shops to minimize costs while ensuring optimal stock availability. The research underscores the importance of adaptive inventory management strategies in a dynamic market characterized by fluctuating prices and availability. The novel model contributes to the literature by providing a more accurate representation of inventory management challenges faced by automotive repair shops. The incorporation of realistic purchasing constraints enhances the model’s practicality, making it a valuable tool for practitioners seeking to optimize inventory operations in a dynamic environment.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0201437