关键词: 连铸机, 生产调度, 开浇决策, 多目标优化, 改进的非支配排序遗传算法

Abstract: For the integrated decision making of charge selection and sequencing in the batch plan as well as the casting start time for continuous casters,a multi-objective optimization model was developed.The objectives were set to minimize the penalty of production batch plan implementation in steel plans,the amount of metal stocked in production line and the non-effective usage amount of high quality hot metal.According to the characteristics of model,an improved solving multi-objective evolutionary algorithm was derived based on Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ).The chromosome was represented with the serial number of all charges in the charge batching pool to decrease the invalid searching space of solution.To reduce the computational complexity,the computation order of elitist solution in classical NSGA-Ⅱ was modified and the crowding distance calculation times for individuals were restricted.A fuzzy selection method was employed to choose the final solution among Pareto solutions.Computational tests on the real operation data of a steel plant showed that the proposed multi-objective optimization model was conducive to the stable control of charge's casting cycle on continuous casters,and the modified algorithm was better than the classical NSGAⅡ and Strength Pareto Evolutionary Algorithm-Ⅱ (SPEA-Ⅱ).

Key words: continuous caster, production scheduling, casting start time decision, multi-objective optimization, non-dominated sorting genetic algorithm-Ⅱ