遗传算法的改进及在钢铁企业煤气调度中的应用  

Application of Improved Genetic Algorithm in Gas Dispatching of Iron and Steel Enterprise

作　　者：李智[1] 苏福永[1] 温治[1] 刘训良[1] 

机构地区：[1]北京科技大学机械工程学院,北京100083

出　　处：《东北大学学报（自然科学版）》2014年第5期645-649,共5页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(51276015)

摘　　要：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,建立了钢铁企业副产煤气使用收益最大的数学模型.同时,针对遗传算法中寻优效率低、寻优方式单一等不足,利用蚁群算法在局部搜索方式上的灵活性和多样性,将蚁群算法的局部搜索过程与遗传算法中的基因变异过程进行了结合,得到了改进的实值遗传算法,并对算法的可行性及准确性进行了数学实验的验证.最后,对某钢铁厂进行了实际的研究,为其生产取得了一定的经济效益.By-product gas is important in iron ＆ steel industry, so a maximum benefit objective model was built based on the analysis of characteristic and relationships of important by-product equipments. Meanwhile, considering the deficiencies and shortcomings of genetic algorithm, which may lead to the low efficiency of the optimization and local search ability, the mutation process with the movement process of ant colony algorithm was replaced to solve the calculation of the model. The proposed model was flexible in the local searching styles, and easy to combine with other algorithms, Finally, the algorithm was successfully tested by means of PC simulations. By the achieved method, the optimization dispatching model of an iron ＆ steel industry was solved, leading to a better benefit.

关 键 词：副产煤气 数学模型 蚁群算法 局部搜索 遗传算法 

分 类 号：TK321[动力工程及工程热物理—热能工程]