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油气集输系统障碍拓扑布局优化设计方法
引用本文:魏立新,刘扬. 油气集输系统障碍拓扑布局优化设计方法[J]. 石油学报, 2006, 27(6): 120-124. DOI: 10.7623/syxb200606031
作者姓名:魏立新  刘扬
作者单位:大庆石油学院石油工程学院 黑龙江大庆 163318
基金项目:中国石油天然气集团公司资助项目
摘    要:针对油气集输系统障碍拓扑布局优化问题,以管线长度最短为目标函数,以节点隶属关系唯一性,节点处理能力和几何位置等为约束条件,建立了二级混合规划数学模型。根据模型的结构特点,将优化设计问题分为布局层和分配层,并采用混合遗传模拟退火算法进行求解。采用实数对染色体进行编码,采用了自由交叉和优势交叉相结合、精细变异和强烈变异交替使用的方式进行遗传操作,并实施了基于Metropolis判别准则的复制策略和最优保存策略,有效地提高了算法的优化性能。实例计算表明,所建立模型准确,优化算法有效。

关 键 词:油气集输系统  拓扑优化  遗传算法  模拟退火  数学模型  
文章编号:0253-2697(2006)06-0120-05
收稿时间:2006-01-23
修稿时间:2006-01-232006-05-08

Obstacle topological layout optimization design of oil-gas gathering and transferring system
Wei Lixin,Liu Yang. Obstacle topological layout optimization design of oil-gas gathering and transferring system[J]. Acta Petrolei Sinica, 2006, 27(6): 120-124. DOI: 10.7623/syxb200606031
Authors:Wei Lixin  Liu Yang
Affiliation:College of Petroleum Engineering, Daqing Petroleum Institute, Daqing 163318, China
Abstract:A bilevel hybrid topological layout optimization model for oil-gas gathering and transferring system was established, in which the minimal pipeline length was taken as the objective function, and the unique memberships, the processing capacity and geo metrical position of nodes were taken as the constraint conditions. The model concerns the hybrid optimization design problem with disperse and continuous variables. According to the configuration characteristics of the model, the optimization problem was divided into location and allocation layers, and solved by hybrid genetic simulated annealing algorithm. In order to improVe the optimization performance, the chromosome was coded in real number, while free crossover and dominating crossover were combined with each other, and subtle mutation and violent mutation were alternated. The reproduction strategy based on Metropolis criteria and elitist preserved strategy were also applied. Practical example indicated the accuracy of the optimization model and feasibility of the algorithm.
Keywords:oil-gas gathering and transferring system   topological optimization  genetic algorithm   simulated annealing   mathematical model
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