Development of an information fractal to optimise inventory in the supply network

The aim of this research paper is to develop a new conceptual framework for an information fractal to optimise inventory including safety stock, cycle stock and prevent stock out at lowest logistics cost and further enhance integration within the network. The proposed framework consists of two levels; top and bottom level fractals. Fractals in the bottom level analyse demand, optimise safety stock and then transmit output to the top level fractal. Fractals in the top level investigate different replenishment frequencies to determine the optimum cycle stock for each fractal in the bottom level. The proposed conceptual framework and a hypothetical supply network are implemented and validated using mathematical modelling and Supply Chain GURU Simulation Software; in order to optimise inventory in the supply network during the demand test period. Experimental factorial design and statistical techniques (MANOVA) are used to generate and analyse the results.