A dynamic decision approach for supplier selection using ant colony system

Purpose: This study based on the attribute-based ant colony system (AACS) to construct a platform to examine the critical factors for decision making in a dynamic business environment in order to select the appropriate suppliers. Design/methodology/approach: This study focuses on how to search for optimal suppliers in a similar fashion to how the optimal route can be found. The AACS is based on the ant colony system (ACS) algorithm, which is then modified to achieve the adaptive optimal system used to set the policy for companies to select their suppliers, as the researcher (as like source node) and chosen supplier's attributes to be conditions of research (destination node). Findings: At first, we provide the development of policy model and can effective and immediately to choose the best suppliers from the company's policy and the attribute of suppliers. Secondly, this policy system is based on the platform of AACS and also modifies the new heuristics algorithm. Research limitations/implications: There are two limitations with this study. First, the criteria for the policy and attribute numbers and sequence for suppliers must be same. Secondly, the score has evaluated by the buyer company before the decision group to use which one policy. Practical implications: The value of this study divides two points; the parameters of AACS platform are adjustment for the buyer decision policy from dynamically business environment and the AACS can find an optimal solution from the decision policy. Originality/value: AACS according to the decision group's policy to enter parameters in order to find the adaptive solution for buyer business firm to find their finest suppliers. (C) 2010 Elsevier Ltd. All rights reserved.