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针对蜂群算法存在的收敛速度慢以及容易陷入局部最优的缺陷,利用一种自适应窗口机制,改进蜂群算法中引领蜂搜索蜜源的方式,得到一种改进的多目标人工蜂群算法(MOABC)。进而,以预防打滑和轧制能耗最小为目标,建立轧制规程多目标优化模型。最后,将改进的多目标蜂群算法(MOABC)应用到某5机架冷连轧机,进行多目标轧制规程优化设计。仿真结果表明,改进的MOABC算法能够获得更好的近似pareto前沿,和原规程相比,有效地降低了2个目标函数的值。
Aiming at the low convergence speed and the defect that the bee colony algorithm is easy to fall into the local optimum, an adaptive window mechanism is used to improve the way of bee searching honeybee in the bee colony algorithm. An improved multi-objective artificial bee colony algorithm MOABC). Furthermore, a multi-objective optimization model of rolling schedule is established with the aim of preventing slippage and minimizing energy consumption of rolling. Finally, the improved multi-objective bee colony algorithm (MOABC) was applied to a 5-stand tandem cold rolling mill to optimize the multi-objective rolling schedule. The simulation results show that the improved MOABC algorithm can obtain a better approximation pareto front, which effectively reduces the values of two objective functions compared with the original one.