Solving Hot Rolling Batch Planning Problem by Genetic Algorithm

To solve the hot rolling batch planning problem in production scheduling of iron and steel enterprises, a hot rolling batch planning model is formulated based on multiple travelling salesmen problem(MTSP) model. The objective is to minimize the total limit penalty value of adjacent stripped steels in width, thickness and hardness. The main constraints include jumps in width, thickness and hardness between adjacent stripped steels, which are essential for actual steel production process. An improved genetic algorithm is designed to solve the model. The proposed model and algorithm is verified by the data from iron and steel enterprise. Compared with traditional manual planning method, the new method obtains better results and efficiency, which is a big improvement for hot rolling batching planning problem.