A Multi-Agent Model for Supply Chain Ordering Management: An Application to the Beer Game

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The American Production and Inventory Control Society Dictionary defines the term supply chain (SC) as “the process from the initial raw materials to the ultimate consumption of the finished product linking across supplier–user companies.” Supply chain management (SCM) literature covers wide range of areas such as logistics, production, scheduling, facility location, procurement, inventory management, ordering management, and so on. Due to the increasing competition in today’s global market, business enterprises are forced to improve their supply chains to reduce inventory cost and enhance customer service levels (Wang & Shu, 2005; Giannoccaro, 2003). Supply chain ordering management (SCOM), which is the main concern of this book chapter is an integrated approach to determine the ordering size of each actor of SC to the upstream actor aiming to minimize inventory costs of the whole supply chain. SCOM is focused on the demand of the chain aiming to reduce inventory holding costs, lower slacks, improve customer services, and increase the benefits throughout the entire supply chain (Chaharsooghi et al., 2008). The observed performance of human beings operating supply chains, whether in the field or in laboratory settings, is usually far from optimal from a system-wide point of view (Lee & Whang, 1999; Petrovic, 2008). This may be due to lack of incentives for information sharing, bounded rationality, or possibly the consequence of individually rational behaviour that works against the interests of the group. In a few cases, the researchers' focus is placed on the coordination and integration of inventory policies between more than three stages (Kimbrough et al., 2002; Mahavedan et al., 1997; Petrovic et al., 1999; Wang & Shu, 2005). When there is no coordination among supply chain partners, each entity makes decision based on its own criteria, which results in local optimization as opposed to global optimum. So called Beer game (Sterman, 1989) is a well-known example of supply chain which has attracted much attention from practitioners as well as academic researchers. Optimal parameters of the beer game ordering policy, when customers demand increases, have been analyzed in two different situations. It has been shown that minimum cost of the chain (under conditions of the beer game environment) is obtained when the players have