期刊文献+

多源注水系统泵站优化调度的双重编码混合遗传算法 被引量:10

Dual Coding Hybrid Genetic Algorithm for Optimal Schedule of Pumping Stations in Multi-Sources Water Injection System
在线阅读 下载PDF
导出
摘要 以耗电量最小为目标函数,排量、压力等限制为约束条件,建立了多源注水系统泵站优化调度数学模型.遗传算法采用了二进制编码和实数编码相结合的双重编码,并调整了适应函数,采用随机多父辈适应函数值加权交叉和多种变异操作,结合模拟退火算法,给出了初温的确定方法,形成了混合遗传算法.该算法能够有效地提高收敛速度,避免早熟收敛.同时,在操作过程中给出了泵排量的处理方法,使各水量约束条件得到满足,减少了不可行解的产生.算例显示了该优化方法的有效性. A mathematical model for the optimal schedule of water injection pumping stations is established, in which the minimum electric power consumption is taken as the objective function, and the restrictions to the displacement and pressure are taken as constraint conditions. In the genetic algorithm dual coding is adopted, the fitness function is adjusted, and random pareut-number fitness-weighted cross and many mutation inethods are adopted. The simulated annealing algorithm is combined to give the method of determining initial temperature, thus the hybrid genetic algorithln is formed. It can improve the speed of convergence and avoid premature convergence. A proccssing method of displacement is proposed, so the displacement restrictions are satisfied and the number of infeasible solutions is reduced. Example shows that the algorithm is efficient.
机构地区 大庆石油学院
出处 《自动化学报》 EI CSCD 北大核心 2006年第1期154-160,共7页 Acta Automatica Sinica
基金 黑龙江省自然科学基金(E2004-19)资助~~
关键词 多源注水系统 优化调度 泵站 混合遗传算法 双重编码 Multi-sources water injection system, optimal schedule, pulnping station hybrid genetic algorithm, dual coding
  • 相关文献

参考文献6

二级参考文献31

  • 1陈淼鑫,刘铁男,司光宇.大型注水系统的建模、优化和控制[J].石油规划设计,1995,6(3):34-36. 被引量:17
  • 2丰国斌.油田注水系统节能[J].石油规划设计,1996,7(2):7-9. 被引量:66
  • 3严煦世 赵洪宾.给水管网理和论计算[M].北京:中国建筑工业出版社,1986.12.
  • 4李光泉 郑丕谔 仲伟俊.城市供水管网系统的优化调度[J].系统工程学报,1987,(1).
  • 5[1]Zbigniew Michalewicz. Genetic Algorithms+Data Structures=Evolution Programs[M].Berlin: Springer-Verlag, 1996
  • 6[2]Goldberg D E.Genetic Algorithm in search,Optimization,and Machine learning[M].Massachusetts: Addison-Wesley, Reading, 1989
  • 7[3]Eshelman L J,Caruana R A,Schaffer J D.Biases in the Crossover Landscape[C].In:Schaffer,J D Eds. Proceedings of the 3rd International Conference on Genetic Algorithms,CA:Morgan Kaufmann Publishers,San Mateo, 1989:10~19
  • 8[4]Syswerda G.Uniform Crossover in Genetic Algorithms[C].In:Schaffer J D Eds. Proceedings of the 3rd International Conference on Genetic Algorithms. CA:Morgan Kaufmann Publishers,San Mateo, 1989:2~9
  • 9[5]Spears W M, De Jong K A.On the Virtues of Parametrized Uniform Crossover[C].In:Belew R, Booker LEds. Proceedings of the 4th International Conference on Genetic Algorithms,CA:Morgan Kaufmann Publishers,San Mateo, 1991:230~236
  • 10[6]Muhlenbein H,Voigt H-M.Gene Pool Recombination for the Breeder Genetic Algorithm[C].In:Proceedings of the Metaheuristics International Conference.Colorado:Breckenridge, 1995:19~25

共引文献72

同被引文献102

引证文献10

二级引证文献90

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部