Optimization setting control method based on BFO and CBR for laminar cooling water

Aiming at the target optimization problem in the laminar cooling process, we proposed a laminar cooling water optimization setting control method, integrating improved bacterial foraging optimization (BFO) algorithm and case-based reasoning (CBR) technology. We construct two layers structure of dynamic optimization to realize offline optimization and online reasoning. The simulation results with industrial operating data showed the effectiveness in searching optimized cooling water consumption in varying working condition. The proposed method has the ability to adjust the water consumption setting value in time and the strip coiling temperature is controlled in the target range.