A decentralized collaborative replenishment decision-making model in the automobile supply chain sector

Fulfilling the order requirements from costumers at the right time and with minimum costs has been an important study approached by supply chain management researchers. One of the main aspects addressed is the replenishment process which considers demand forecasting, customer orders, inventory levels, and production and transport planning. Generally, replenishment processes are carried out traditionally by no considering sharing information among the nodes and neither by coordinating the transport planning with the production planning. With this in mind, this paper mainly focuses on proposing a novel decentralized collaborative replenishment model applied to the automobile sector in order to support the decision-making process among automobile supply chain decision-makers. This has been based on the replenishment information that is already used by supply chain members. This work hypothesizes that a collaborative replenishment process could imply a reduction in inventory levels and, in turn, in inventory costs, and that the number of trucks needed to support the replenishment process would be optimized.