The convergence of physical and online retailing paves the way for the emergence of a retailing omnichannel. Omnichannel retailing supply chain management is challenged by uncertainty, oscillations in sales volume and supply-demand incompatibility. Dealing with those challenges requires the adoption of strategies focused on complex systems that properly employ new information and communication technologies as well as intelligent decision methods. In this context, this research paper aims to propose a reference model for a predictive and adaptive management approach for omnichannel retailing supply chain combining machine learning to minimize uncertainty and simulation based optimization to handle supply-demand synchronization.
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