Designing an Intelligent Warehouse Based on Genetic Algorithm and Fuzzy Logic for Determining Reorder Point and Order Quantity

Abstract

We develop a model to determine the reorder point and the optimal order quantity in a warehouse. Due to the maintenance costs, it is better to consider the order time period and the order quantity to prevent excessive inventory storage while reducing the cost on the other hand. In our study, we employ fuzzy logic as time decision aid and Genetic Algorithm for optimal order quantity. The decision making process is performed in an application software designed for a diary firm.

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