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Global supply chain networks are undergoing a transition with mass customization policies, shrinking profit margins, non deterministic order behavior together with other uncertainties. Self-organized supply chain networks (SCN) are offering an alternative as they enjoy the flexibility needed to respond in real time. In this paper, we describe the pre-requisites for the selforganization of a SCN. This paper also proposes a nonlinear model for the SCN. A brief state of the art towards the selforganized supply chains is presented illustrating the theory that is in practice. It is shown that synchronization is a vital step towards the self-organization and different aspects of synchronization are discussed. The major contribution is towards the analog simulation of the supply chain model in consideration using the cellular neural networks (CNN). The performance comparison with the numerical simulation is also discussed. Today companies expect to use the modern information and communication technologies to achieve the efficient supply chain networks. In this work we are dealing with the depth and reliability of information available with these technologies coupled with the individual objectives of the companies and proposing an analog simulation based approach to provide solution in real time. Our findings concern future supply chain management practices, a new research directions.

Self-organized supply chain networks: theory in practice and an analog simulation based approach