This disclosure provides a system and method for concurrent dynamic optimization of a replenishment decision in a networked node environment by receiving at least one current state attribute associated with the networked node environment at a predetermined time interval; obtaining an optimized entity actionable matrix by mapping the at least one of current state attribute and an associated actionable entity; computing a predictive replenishment matrix for an impending cycle of the networked node environment based on the optimized entity actionable matrix; identifying a reward function for the predictive replenishment matrix; and determining the replenishment suggestive actionable element based on the reward function. The reward function includes a computation of overall cost with regard to a realized revenue associated with aggregation of the plurality of nodes.