Recent economic and environmental constraints push supply chain management systems to adopt closed-loop supply chain operating modes that have to address very complex problems including the end-user quality of services, environmental considerations, and daily transportation time variations. Relevant and challenging research areas require a proper coordination between the data provider software (Transport Management Software) and the operational research tool in charge of trip definition. This abstract proposes a decision support system applied to the Vehicle Routing Problem able to tackle very large instances with real-life constraints. Our contribution is to propose an architecture that handle both static resolution prior to the completion of routes and update them in a dynamical context during their completions. This is implemented through a REST based API using numerous state-of-the-art operational research methods. Moreover, this system in used in practice by the Mapotempo company.