Fuzzy inference systems and inventory allocation decisions: Exploring the impact of priority rules on total costs and service levels

- This paper assesses inventory allocation decisions in light of fuzzy inference systems.
- It builds upon the scant previous studies in this field of knowledge.
- Priority indexes are developed based on a comprehensive total cost structure.
- The proposed approach outperforms specially in terms of total costs.
- Results are robust for larger retail networks.

Inventory allocation decisions in a distribution system concern issues such as how much and where stock should be assigned to orders in a supply chain. When the inventory level of an inventory point is lower than the total number of items ordered by lower echelons in the chain, the decision of how many items to allocate to each ``competing'' order must take into consideration the trade-off between cost and service level. This paper proposes a decision-support system that makes use of fuzzy logic to consider inventory carrying, shortage and ordering costs as well as transportation costs. The proposed system is compared through simulation with three other inventory allocation decision support models in terms of cost and service levels achieved. Conclusions are then drawn.