An information fractal for supply network inventory optimisation

SAAD, Sameh and BAHADORI, Ramin (2016). An information fractal for supply network inventory optimisation. In: AFFENZELLER, Michael, LONGO, Francesco, MERKURYEV, Yury, BRUZZONE, Agostino G. and PIERA, Miquel Angel, (eds.) 18th International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation (HMS 2016) : held at the 13th International Multidisciplinary Modeling and Simulation Multiconference (I3M 2016) : Larnaca, Cyprus, 26-28 September 2016. Red Hook, NY, Curran Associates, Inc. (2016), 28-34.

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Abstract

This paper develops a new conceptual framework for an information fractal to optimise inventory across the supply network by identifying the optimum safety stock, inventory policy and cycle stock with the lowest logistics cost as well as out of stock prevention. The proposed framework consists of two levels: top and bottom level fractals. Fractals in the bottom level analyse demand, optimise safety stock and recommend an inventory policy. Then transmit output to the top level fractal to investigate the effect of different replenishment frequencies to determine the optimum cycle stock for each fractal in the bottom level by integrating the inventory holding costs and transportation costs to minimise the logistics cost. The proposed framework provides a systematic method through which practitioners are able to decide upon the demand analysis, safety and cycle stock optimisation

Item Type: Book Section
Additional Information: Paper originally presented at the 18th International Conference on Harbor, Maritime & Multimodal Logistics Modelling and Simulation, September 26-28, 2016, Larnaca, Cyprus. 27th September 2016.
Research Institute, Centre or Group: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Systems Modelling and Integration Group
Departments: Arts, Computing, Engineering and Sciences > Engineering and Mathematics
Depositing User: Sameh Saad
Date Deposited: 18 Jan 2017 14:04
Last Modified: 13 Jun 2017 13:54
URI: http://shura.shu.ac.uk/id/eprint/14015

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