摘要
提出一种寻优性能良好的优选优生进化算法,该方法与实数编码、线性交叉的遗传算法相比,计算复杂性低,离线性能和在线性能都有较大的改进,全局寻优能力明显提高。基于优选优生进化算法,采用测量误差为污染正态分布的数据整定与过失误差同步检测的方法对常减压装置进行稳态流量整定,提高了数据的一致性。
A novel evolution algorithm with select-best and prepotency operator, named as select best and prepotency evolution algorithm （SPEA）, was proposed. The select-best and prepotency genetic operator is defined as follows： each individual of the population has the same chance to select the best individual within the some range around itself and crossover with the selected individual to produce the new individuals, then the best new individual is selected as the individual of the next generation. To compare the performances of SPEA with those of the traditional genetic algorithm （TGA）, SPEA and TGA were applied to search the global optimum solution of analytical function. The results demonstrated that SPEA spent less CPU time than that of TGA; the on-line and off-line performance, and local search ability of SPEA were superior to that of TGA;the probability of SPEA to find the global optimal solution was larger than that of TGA. Furthermore, based on SPEA, a synchronous arithmetic including data reconciliation and lapse error detection was employed for the steady-state flow data reconciliation of crude oil distillation, and satisfactory results were obtained.
出处
《石油炼制与化工》
CAS
CSCD
北大核心
2005年第7期64-68,共5页
Petroleum Processing and Petrochemicals
基金
上海启明星项目(04QMX1433)
国家973项目(2002CB312200)
国家863项目(2002AA412110)
