Nash Negotiation Method of Conflict Resolution for MSC Production Marketing Coordination Based on Multi-Agent
In the face of increasingly market competition and diversified demand, manufacturers and dealers of Manufacturing Supply Chain (MSC) pay great effort to achieve production marketing coordination. However, it often generates conflicts in the process of pro
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Abstract. In the face of increasingly market competition and diversified demand, manufacturers and dealers of Manufacturing Supply Chain (MSC) pay great effort to achieve production marketing coordination. However, it often generates conflicts in the process of production marketing coordination. For this kind of conflict problem, Multi-Agent technology is introduced. Enterprises of the supply chain are represented by Agents. The conflicts among Agents are resolved through Nash negotiation. A model of Nash Negotiation based on Agents is established. The conflict point of negotiation is determined by Stackelberg differential game. A Memetic Algorithm is proposed to solve the model. Finally, the validity of the algorithm and the model is verified by numerical experiment. Keywords: Supply chain based on Multi-Agent, Production marketing coordination, Conflict, Nash negotiation, Memetic Algorithm, Differential game.
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Introduction
Production marketing coordination includes core businesses of supply chain, and it is the most important activity of manufacturing [1]. Because each member of the supply chain is independent individual, the operation among members in supply chain often has the characteristics of autonomy, distribution and so on, which leads to that conflicts in the process of production marketing coordination are hard to avoid [2]. If conflicts are not resolved in a timely and effective way, it will affect the effect of coordination and reduce the competitiveness of supply chain [3]. Traditional supply chain management can't resolve the problem of conflict in production marketing coordination effectively. With the development of the distributed object technology and artificial intelligence technology, it has been an important method to research and implement supply chain management that uses Multi-Agent technology to simulate, optimize and control the operation of supply chain [4]. The conflicts in production marketing coordination for supply chain based on Multi-Agent have drawn the attention of some scholars. Zhang establishes a coordination model of supply chain based on Multi-Agent to solve order conflicts, K. Liu et al. (Eds.): ICISO 2014, IFIP AICT 426, pp. 378–387, 2014. © IFIP International Federation for Information Processing 2014
Nash Negotiation Method of Conflict Resolution
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and puts forward a negotiation method based on fuzzy theory and Bayesian learning theory to solve the model [5]. For the problem of order fulfillment, Lin establishes a coordination model of Multi-Agent supply chain based on distributed constraint satisfaction, proposes a conflict resolution method based on the negotiation and analyzes the effect of constraint satisfaction algorithm under different form of demand [6]. Zheng analyzes the generating mechanism of conflict of supply chain from the aspect of information coordination, explores the application of multi-Agent system in supply chain management and establishes a supply chain model based on Multi-Agent which can solve the problem of asymmetric information [7].
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