Incorporating DCSP Algorithms into Multi-agent System for Supply Chain Collaboration - A Case Study for Manufacturing Supply Chain

Nowadays, products are expected to have features such as more innovative, multi functional, high quality, and low price because of the changing of consumers' purchasing behavior. This phenomenon forces manufacturing industries to lower their cost, shorten innovation time, and collaborate with companies in their supply chain. However, it is difficult to collaborate among supply chain companies because of the wide distribution and limitations of companies. Due to the characteristics of agents, such as autonomous ability, social ability (communicative), applying multi-agent system (MAS) to supply chain collaboration has been demonstrated with fascinating results. Furthermore, supply chain collaboration problem can be regarded as a distributed constraints satisfaction problem (DCSP) since constraints are diverted in supply chain echelons. Therefore, incorporating DCSP techniques into MAS will form the basis for achieving better decision among supply chain collaboration. However, related research is lack and to be wanting. Hence, this paper develops a DCSP algorithm that can be appropriately applied for manufacturing (OEM) supply chain collaboration. Our research finds that using a suitable DCSP algorithm, time and cost can be reduced in manufacturing supply chain and better effectiveness can be achieved for future competition.