化工学报 ›› 2012, Vol. 63 ›› Issue (9): 2965-2971.DOI: 10.3969/j.issn.0438-1157.2012.09.047

• 过程系统工程 • 上一篇    下一篇

改进的膜计算仿生优化算法及在汽油调和中的应用

赵进慧, 柴天佑, 周平   

  1. 东北大学流程工业综合自动化国家重点实验室, 辽宁 沈阳 110819
  • 收稿日期:2012-06-19 修回日期:2012-06-30 出版日期:2012-09-05 发布日期:2012-09-05
  • 通讯作者: 赵进慧
  • 作者简介:赵进慧(1974-),女,博士后。
  • 基金资助:

    国家博士后科学基金项目(2011M500567);中央高校基本科研业务费(N100508001);国家自然科学基金项目(61174187);东北大学科研启动费(29321006)。

Modified bio-inspired algorithm based on membrane computing and application in gasoline blending

ZHAO Jinhui, CHAI Tianyou, ZHOU Ping   

  1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, Liaoning, China
  • Received:2012-06-19 Revised:2012-06-30 Online:2012-09-05 Published:2012-09-05
  • Supported by:

    supported by the China Postdoctoral Science Foundation(2011M500567),the Fundamental Research Funds for the Central Universities(N100508001),the National Natural Science Foundation of China(61174187)and the Scientific Research Foundation of Northeastern University(29321006).

摘要: 为提高膜计算仿生优化算法在求解流程工业复杂优化问题的计算性能,提出一种改进的膜计算仿生优化算法。该算法采用一个新的不确定性提取规则取代改进前的提取规则。4个有约束标准测试函数被用于检验该算法的计算性能,计算结果及对比显示了改进算法在鲁棒性和效率等方面优于改进前算法。改进算法应用于汽油调和优化问题,更高利润的配方及算法的计算效率证实了改进算法的优越性和实用性。

关键词: 膜计算, 复杂优化问题, 优化, 油品调和

Abstract: Aiming at improving the computational performance of bio-inspired algorithm based on membrane computing(BIAMC)in solving complex optimization problems in process manufacturing,a modified bio-inspired algorithm based on membrane computing(MBIAMC)is proposed.In MBIAMC,a new indeterministic abstraction rule is applied which substitutes the abstraction rule of BIAMC,and the algorithmic framework and other rules are inherited from BIAMC.For solving constrained optimization problems,the quadratic penalty function method is introduced in MBIAMC.Four constrained benchmark functions are used to evaluate computational performance of MBIAMC.The results and comparison with other two algorithms handling constraints problems reveal that MBIAMC is efficiency and superiority to BIAMC in accuracy and robustness.As a case study,MBIAMC is used to solve gasoline blending optimization problem,the better recipes and its lower computational cost validate its higher efficiency and more practicability.

Key words: membrane computing, complex optimization problems, optimization, gasoline blending

中图分类号: