Inventory Control Using Fuzzy Inference System and Adaptive Neuro Fuzzy Inference System under Uncertain Conditions

Abstract

Supply chain management plays a significant role for running business efficiently, as it integrates management of
materials and information flows between supply chain parties Fuzzy Inference System (FIS) and Adaptive Neuro
Fuzzy inference system (ANFIS) are expert systems widely used to deal with imprecise and vague data. In this paper
FIS and ANFIS are implemented to deal with the uncertainty regarding demand, lead time and inventory level in
continuous inventory control system in order to obtain the optimal order quantity and reorder point. These two
models are compared with Economic Order Quantity (EOQ) model at different service level to study their impacts on
the inventory costs. A case Study of Yemen Company for Industry and Commerce has been selected in this paper.
The simulation results showed the superiority and efficiency of the proposed FIS and ANFIS models in comparison
to stochastic EOQ model with7 %saving of total inventory cost and no shortages with expectation of raising the
customers’ loyalty.