Multi-objective Optimal Scheduling of Stacker–reclaimers Using the RPCNSGA II Algorithm

Abstract

Background: The stacker-reclaimer is a device for transporting bulk materials in ironmaking raw material yards. An excellent scheduling plan can provide a good raw material supply basis for steel enterprises. It is of great significance to improve the efficiency of steel production, reduce unnecessary operating waste and management costs, and realize scientific management of steel production. Objective: This patent aims to optimize the total material transportation time and equipment utilization balance within a single operation plan of the stacker-reclaimer involved in the raw material yard. Methods: A multi-objective optimization model for the stacker reclaimer is established, and the Reverse learning and Population Competitive-NSGA II (RPC-NSGA II) algorithm is introduced for solving. This algorithm uses reverse learning and population competition mechanism to improve the convergence and diversity of the algorithm. Results: The proposed method was experimentally verified in a raw material yard with a 360m2 sintering machine and a bulk material port. The method converges well and obtains a Pareto front with a uniform distribution. Compared with the actual scheduling plan, the scheduling plan under the optimal compromise solution reduces the maximum completion time by 11.23 minutes and increases the equipment utilization balance rate by 11.70%. Conclusion: The proposed method can consider the material transportation time and equipment utilization balance, which is of great significance for the optimized use of the stacker reclaimer in steel enterprises and the quality assurance of raw material supply