Title :
Coke oven pushing plan optimization scheduling research based on improved ant colony algorithm
Author :
Tao, Wen-hua ; Gao, Xian-wen ; Sun, Ao
Author_Institution :
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Abstract :
Coke oven pushing optimization scheduling plays a important role in coke oven productions, especially in the abnormal operating conditions where sequences disorder problem often happens. In order to solve the sequences disorder problem, Firstly, we establish a coke oven pushing optimization scheduling model by means of the target of achieving the least punishment caused by distance, time and pushing coefficient in restoring normal order process. Secondly, in order to avoid the stagnation of the search in ant colony algorithm, adaptive ant colony optimization algorithm wais used to solve optimization scheduling model. Finally, through the simulation of actual production data, experimental results verified the effectiveness of the algorithm. It has a wide application prospect.
Keywords :
Adaptation models; Ant colony optimization; Job shop scheduling; Optimization; Ovens; Coke oven pushing plan; Improved ant colony algorithm; Optimization scheduling;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7260058