Borja Ponte¹, David de la Fuente², Raúl Pino³, Rafael Rosillo⁴, and Isabel Fernandez⁵

¹ PhD student at the Polytechnic School of Engineering (University of Oviedo), Campus de Viesques s/n, CP 33204, Gijon (Asturias), Spain (e-mail: uo183377@uniovi.es).

² Polytechnic School of Engineering (University of Oviedo), Campus de Viesques s/n, CP 33204, Gijon (Asturias), Spain (e-mail: david@uniovi.es).

³ Polytechnic School of Engineering (University of Oviedo), Campus de Viesques s/n, CP 33204, Gijon (Asturias), Spain (e-mail: pino@uniovi.es).

⁴ Polytechnic School of Engineering (University of Oviedo), Campus de Viesques s/n, CP 33204, Gijon (Asturias), Spain (e-mail: rosillo@uniovi.es).

⁵ Polytechnic School of Engineering (University of Oviedo), Campus de Viesques s/n, CP 33204, Gijon (Asturias), Spain (email: ifq@uniovi.es).

Manuscript received on July 24, 2013.
Accepted for publication on September 30, 2013.

Abstract

Several changes in the macro environment of the companies over the last two decades have meant that the competition is no longer constrained to the product itself, but the overall concept of supply chain. Under these circumstances, the supply chain management stands as a major concern for companies nowadays. One of the prime goals to be achieved is the reduction of the Bullwhip Effect, related to the amplification of the demand supported by the different levels, as they are further away from customer. It is a major cause of inefficiency in the supply chain. Thus, this paper presents the application of simulation techniques to the study of the Bullwhip Effect in comparison to modern alternatives such as the representation of the supply chain as a network of intelligent agents. We conclude that the supply chain simulation is a particularly interesting tool for performing sensitivity analyses in order to measure the impact of changes in a quantitative parameter on the generated Bullwhip Effect. By way of example, a sensitivity analysis for safety stock has been performed to assess the relationship between Bullwhip Effect and safety stock.

Key words: Artificial Intelligence, bullwhip effect, simulation, supply chain management.

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This work was supported by the Government of the Principality of Asturias, through the "Severo Ochoa" Predoctoral Grants for Research and Teaching of the Principality of Asturias.

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