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Demand and Supply Chain Simulation in Telecommunication Industry by Multi-Rate Expert Systems

Authors: Igor Astrov, Andrus Pedai

Abstract:

In modern telecommunications industry, demand & supply chain management (DSCM) needs reliable design and versatile tools to control the material flow. The objective for efficient DSCM is reducing inventory, lead times and related costs in order to assure reliable and on-time deliveries from manufacturing units towards customers. In this paper the multi-rate expert system based methodology for developing simulation tools that would enable optimal DSCM for multi region, high volume and high complexity manufacturing environment was proposed.

Keywords: Inventory Control, Performance Metrics, Demand & supply chain management, expert systems, multi-rate control

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1333873

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References:


[1] Supply Chain Management Research Center.
[Online]. Available: http://www.cio.com/research/scm/edit/012202_scm.html
[2] M. Koch, B. Kleinjohann, A. Schmidt, P. Scheideler, A. Saskevic, E. M├╝nch, A. Gambuzza, O. Oberschelp, and T. Hestermeyer, "Neurofuzzy approaches for self-optimizing concepts and structures of mechatronic systems," in Proc. Int. Conf. Computing, Communications and Control Technologies, Austin, TX, USA, 2004, pp. 263-268.
[3] L. Fausett, Fundamentals of Neural Networks: Architectures, Algorithms, and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1994.
[4] S. J. Russell and P. Norvig, Artificial Intelligence - a Modern Approach. Upper Saddle River, NJ: Prentice-Hall, 1995.
[5] L.A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, no. 3, pp. 338-353, June 1965.
[6] F. Klawonn and E. P. Klement, "Mathematical analysis of fuzzy classifiers," in Advances in Intelligent Data Analysis Reasoning about Data, X. Liu, P. Cohen, M. Berthold, Eds. Berlin: Springer, 1997, pp. 359-370.
[7] M. Koch and O. Oberschelp, "Simulation of self optimizing mechatronical systems with expert system knowledge," in Proc. 5th Asian Control Conf., Melbourne, Australia, 2004, pp. 1437-1445.
[8] M. Wooldridge and N. R. Jennings, "Intelligent agents: theory and practice," The Knowledge Engineering Review, vol. 10, no. 2, pp. 115- 152, June 1995.