An enhanced ant colony optimiser for multi-attribute partner selection in virtual enterprises

Abstract

Increasing global competition drives enterprises, especially small and medium-sized enterprises, to collaborate in order to respond faster to customers’ needs, reduce operating costs, increase capacity, and produce customised products to reach the market quicker. A virtual enterprise (VE) is an important manufacturing paradigm to address this trend in the dynamic global economy. Partner selection is a key issue tightly coupled to the success of a VE coalition, and because of its complexity, it is considered a multi-attribute optimisation problem. In this paper, an enhanced ant colony optimiser (ACO) is proposed to address the partner selection problem. Five attributes (namely, cost, time, quality, reputation, and risk) considering both qualitative and quantitative aspects have been investigated to evaluate the candidate partners. Experiments have been conducted to validate the performance of the enhanced ACO algorithm, and the results show that the enhanced ACO algorithm can produce better results in terms of search accuracy and computing time.

Keywords:

• ACO
• partner selection
• virtual enterprise