This study presents the Chemical Reaction Optimization (CRO) algorithm for making sense of most dependable parameters of the PID controller as an improvement invention for the end-to-end congestion control using the technique of Active Queue Management (AQM) which can safeguard a minute amount of queuing delay. By the use of a set of CRO rules, even though the PI (Proportional-Integral) controller for AQM design improves the solidness, the transitory exhibition of the PI controller isn't at the best, which incorporates the managing time that is excessively long. Therefore, as to win over this drawback, this paper, the PID (Proportional-Integral-Differential) controller is proposed to accelerate the responsiveness of AQM machine. Because of this, lately, researchers have carried out a random search approach which includes Particle swarm optimization (PSO), Grey Wolf Optimizer (GWO), and Genetic Algorithm (GA) to discover the choicest parameters for PID controller. Among modern-day heuristics algorithms, Chemical Reaction Optimization (CRO) turned and it combines functions of both GA and Simulated Annealing (SA) to find worldwide minimal in seeking space. The test model reproduction results effectively show the adequacy of the proposed calculation and its preferences over other current calculations.