Adaptive fuzzy inventory control algorithm for replenishment process optimization in an uncertain environment

Abstract

This paper presents a real case study of warehouse replenishment process optimization on a selected sample of representative materials. Optimization is performed with simulation model supported by inventory control algorithms. The adaptive fuzzy inventory control algorithm based on fuzzy stock-outs, highest stock level and total cost is introduced. The algorithm is tested and compared to the simulation results of the actual warehouse process and classic inventory control algorithms such as Least-unit cost, Part period balancing and Silver-Meal algorithm. The algorithms are tested on historic data and assessed using the Fuzzy Strategy Assessor (FSA). Simulation results are presented and advantages of fuzzy inventory control algorithm are discussed. © Springer-Verlag Berlin Heidelberg 2007.