Abstract:Aiming at the hot rolling batch planning problem of iron and steel enterprises, considering the constraints of the hot rolling production process and the limitation of the same width slab rolling length, a mathematical model of hot rolling batch planning based on multiple traveling salesman problem (MTSP) with uncertain traveling salesman number was established, the optimization goal was to minimize the number of rolling unit plans and minimize the total penalty value caused by the difference of rolling width, thickness, and hardness between the adjacent rolled slabs. Combined with the actual situation of the model, an improved genetic algorithm based on two exchange heuristics was used to solve the problem. Finally, the actual production data of a steel plant was used to carry out the calculation experiments. At the same time, the optimization situation of the traditional genetic algorithm and the improved genetic algorithm was compared and the results were analyzed, this paper verifies the correctness of the model and the effectiveness of the algorithm were verified.
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XING Huo-lin, XU An-jun, WU Shuang-ping, SONG Wei. Optimization model of hot rolling batch planning based on improved genetic algorithm[J]. China Metallurgy, 2021, 31(5): 47-53.
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