改进的蚁群算法在钢铁企业煤气调度的应用  

Application of Improved Ant Colony Algorithm on Scheduling for the By- Produced Gas of Iron & Steel

作　　者：李智[1] 温治[1] 苏福永[1] 楼国锋[1] 

机构地区：[1]北京科技大学机械工程学院,北京100083

出　　处：《控制工程》2013年第6期1185-1188,共4页Control Engineering of China

基　　金：中央高校基本科研业务费专项资金资助(FRF-TP-12-061A)

摘　　要：副产煤气是钢铁企业生产中重要的能源介质,但钢铁生产流程中设备种类和数量繁多,各设备之间耦合关系复杂,因此通过分析钢铁生产中各重要能耗设备的能源使用特征,以及设备之间存在的耦合关系,并建立以煤气使用的收益最大为目标的目标方程,得到了钢铁企业副产煤气使用收益最大的数学模型。同时,采用了蚁群算法这一灵活性和鲁棒性较好的智能方法,并针对其本身可能出现的易于陷人局部最优值的缺陷,进行了局部搜索方式上的改进,较好地适用于所建立的模型,得到了良好的副产煤气分配的方案。结果表明,所建立的钢铁企业副产煤气自动优化调度模型可以对钢铁企业中重要副产煤气消耗设备及副产煤气缓冲存储设备的使用状况进行系统的分析和实时的调度,为钢铁企业实现副产煤气的全自动调度奠定了基础。By product gas is important in Iron ＆ Steel industry. However, the equipment are too many in number and types, and there are complex relationships between them, we build a maximum benefit objective based on the analysis of their characteristic and re lationships in this paper. Meanwhile, we adopted the ant colony algorithm, which has the feather of flexibility and robustness to solve the mathematic model. To overcome the shortcomings of the algorithm, which will easily lead to the local optimum value instead of the global one, we improved the way of its local search, and the dispatching result of gas shows its applicability. The results show that the automatic scheduling model can analyze the status of the equipments which expend or storage the by produced gas, and prorate the by produced gas real time, it will lay the foundation for the fully automatic scheduling of the byproduced gas.

关 键 词：蚁群算法 副产煤气 自动调度 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]