基于改进粒子群算法的油田管网优化  

Optimization of Oilfield Pipe Network Based on Improved Particle Swarm Algorithm

作　　者：孙涛[1,2] 徐明海[1] 

机构地区：[1]中国石油大学(华东)储运与建筑工程学院 [2]中国石油大学胜利学院

出　　处：《油气田地面工程》2016年第7期38-40,44,共4页Oil-Gas Field Surface Engineering

基　　金：国家自然科学基金项目(51276199);中国石油大学胜利学院春晖计划重点项目(KY2015002)

摘　　要：为了节省油气集输管网的投资成本,往往对系统进行优化设计。应用粒子群算法求解油田地面管网的拓扑优化模型,在算法寻优过程中通过对最优粒子的编码进行动态调整,从而改进算法中粒子对最优粒子的跟随方式,使粒子的进化过程变得更加合理。经过实例验证,在相同计算条件下,改进后粒子群算法在求解地面管网优化问题中表现优于原粒子群算法;最后通过与遗传算法进行比较,粒子群算法在相同计算精度下收敛更快,所需迭代次数更少。The system operation should be optimized for saving investment cost of oilfield pipe network. Particle swarm algorithm is used to solve the optimization model of oilfield pipe network. In the process of iteration, the coding of optimal particle can dynamically adjust, thus improved the way ofthe particles flying to the optimal particle, and the evolution of particles becomes more reasonable. The calculation of example shows that, under the same initial conditions, the improved algorithm works more efficiently than the original one. At last, by comparing with the genetic algorithm, particle swarm optimization algorithm under the same calculation accuracy, faster convergence and less number of iterations required.

关 键 词：油田管网 拓扑优化 粒子群算法 遗传算法 

分 类 号：TE86[石油与天然气工程—油气储运工程]