Nazario García Fernández

CÓMO MEJORAR LA EVALUACIÓN DE PROVEEDORES MEDIANTE SISTEMAS DE INFERENCIA BORROSOS

Traditional supplier evaluation models are usually highly dependent on the purchasing managers’ know-how and their subjective judgments. Recent years have witnessed the proposal of many models to assist in this type of evaluation some of which are not eligible for small and medium enterprises (SMEs), due to their complexity and difficulty of implementation. Some others, despite its simplicity, often provide performance problems. The goal of this paper is twofold. It seeks to design a supplier evaluation model to be both, robust enough about their valuation method and easy to implement and use. Among the different existing valuation methods, a fuzzy inference system proves its suitability not only because it achieves the goals of the paper, but also because it demonstrates to be more efficient than other traditional assessment methods -such as weighting factors-, and it is widely accepted in SMEs according to the results of an empirical validation study.

Multiagent Model for Supply Chain Management

There are several circumstances which, in the last two decades, have granted the Supply Chain Management (SCM) a strategic role in the search for competitive advantage. Thus, this paper applies multiagent methodology to optimize the management. We represent the supply chain as a Global Multiagent System, composed of four Multiagent Subsystems, which replicate the behavior of the different levels of the supply chain. Thereby, each member has its own decision-making capacity and seeks to optimize the performance of the supply chain. We will tackle the problem from two complementary perspectives: reducing the Bullwhip Effect, which can be considered as one of the main sources of inefficiencies in the SCM, and minimizing management costs, both from a non collaborative approach, where each level seeks the best solution for himself, and from a collaborative approach, where each level negotiates with the rest looking for the best solution for the whole supply chain.