改进的膜计算仿生优化算法及在汽油调和中的应用

doi:10.3969/j.issn.0438-1157.2012.09.047

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

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

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

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/Abstract

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:

TP18

赵进慧, 柴天佑, 周平. 改进的膜计算仿生优化算法及在汽油调和中的应用[J]. 化工学报, 2012, 63(9): 2965-2971.

ZHAO Jinhui, CHAI Tianyou, ZHOU Ping. Modified bio-inspired algorithm based on membrane computing and application in gasoline blending[J]. CIESC Journal, 2012, 63(9): 2965-2971.

参考文献 16

[1]	Paun G.Computing with membranes[J].Journal of Computer Systems and Science,2000,61(1):108-143
[2]	Ciobanu G,Paun G,Perez-Jimenez J M.Applications of Membrane Computing[M].Berlin:Springer Science & Business,2006:33
[3]	Ionescu M,Paun G,Yokomori T.Spiking neural P systems[J].Fundamenta Informaticae,2006,71(2/3):279-308
[4]	Calude S C,Paun G.Bio-steps beyond Turing[J].Biosystems,2004,77(1/2/3):175-194
[5]	Nishida T Y.An application of P system:a new algorithm for NP-complete optimization problems//Proceedings of 8th World Multi-conference on Systems,Cybernetics and Informations.2004:109-112
[6]	Huang L,He X X,Wang N,Xie Y.P system based multi-objective optimization algorithm[J].Progress in Natural Science,2007,17(4):458-465
[7]	Huang L,Wang N,Zhao J H.Multiobjective optimization for controllers[J].Acta Automatica Sinica,2008,34(4):472-477
[8]	Zhao J,Wang N.A bio-inspired algorithm based on membrane computing and its application to gasoline blending scheduling[J].Computers and Chemical Engineering,2011,35(2):272-283
[9]	Zhang G X,Gheorghe M,Wu C Z.A quantum-inspired evolutionary algorithm based on P systems for knapsack problem[J].Fundamenta Informaticae,2008,87(1):93-116
[10]	Chen A,Chootinan P.Constraint handling in genetic algorithms using a gradient-based repair method[J].Computers&Operations Research,2006,33(8):2263-2281
[11]	Lu H Y,Chen W Q.Self-adaptive velocity particle swarm optimization for solving constrained optimization problems[J].Journal of Global Optimization,2008,41(3):427-445
[12]	Zhao X Q,Rong G.Blending scheduling based on partial swarm optimization algorithm//Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration(IRI-2004).2004:618-622
[13]	Mendez C A,Grossmann I E,Harjunkoski I,Kabore P.A simultaneous optimization approach for off-line blending and scheduling of oil-refinery operations[J].Computers and Chemical Engineering,2006,30(4):614-634
[14]	Li P,Wendt M,Wozeny G.Optimal production planning for chemical processes under uncertain market conditions[J].Chemical Engineering and Technology,2004,27(6):641-651
[15]	Jia Z Y,Ierapetritou M.Mixed-integer linear programming model for gasoline blending and distribution scheduling[J].Industrial&Engineering Chemistry Research,2003,42(4):825-835
[16]	Singh A,Forbes J F,Vermeer P J,Woo S S.Model-based real-time optimization of automotive gasoline blending operations[J].Journal of Process Control,2000,10(1):43-58

改进的膜计算仿生优化算法及在汽油调和中的应用

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

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献 16

相关文章 15

编辑推荐

Metrics

本文评价

[1]	杨欣, 王文, 徐凯, 马凡华. 高压氢气加注过程中温度特征仿真分析[J]. 化工学报, 2023, 74(S1): 280-286.
[2]	陈哲文, 魏俊杰, 张玉明. 超临界水煤气化耦合SOFC发电系统集成及其能量转化机制[J]. 化工学报, 2023, 74(9): 3888-3902.
[3]	齐聪, 丁子, 余杰, 汤茂清, 梁林. 基于选择吸收纳米薄膜的太阳能温差发电特性研究[J]. 化工学报, 2023, 74(9): 3921-3930.
[4]	何松, 刘乔迈, 谢广烁, 王斯民, 肖娟. 高浓度水煤浆管道气膜减阻两相流模拟及代理辅助优化[J]. 化工学报, 2023, 74(9): 3766-3774.
[5]	邢雷, 苗春雨, 蒋明虎, 赵立新, 李新亚. 井下微型气液旋流分离器优化设计与性能分析[J]. 化工学报, 2023, 74(8): 3394-3406.
[6]	陈国泽, 卫东, 郭倩, 向志平. 负载跟踪状态下的铝空气电池堆最优功率点优化方法[J]. 化工学报, 2023, 74(8): 3533-3542.
[7]	刘文竹, 云和明, 王宝雪, 胡明哲, 仲崇龙. 基于场协同和耗散的微通道拓扑优化研究[J]. 化工学报, 2023, 74(8): 3329-3341.
[8]	张曼铮, 肖猛, 闫沛伟, 苗政, 徐进良, 纪献兵. 危废焚烧处理耦合有机朗肯循环系统工质筛选与热力学优化[J]. 化工学报, 2023, 74(8): 3502-3512.
[9]	诸程瑛, 王振雷. 基于改进深度强化学习的乙烯裂解炉操作优化[J]. 化工学报, 2023, 74(8): 3429-3437.
[10]	吴文涛, 褚良永, 张玲洁, 谭伟民, 沈丽明, 暴宁钟. 腰果酚生物基自愈合微胶囊的高效制备工艺研究[J]. 化工学报, 2023, 74(7): 3103-3115.
[11]	汤晓玲, 王嘉瑞, 朱玄烨, 郑仁朝. 基于Pickering乳液的卤醇脱卤酶催化合成手性环氧氯丙烷[J]. 化工学报, 2023, 74(7): 2926-2934.
[12]	文兆伦, 李沛睿, 张忠林, 杜晓, 侯起旺, 刘叶刚, 郝晓刚, 官国清. 基于自热再生的隔壁塔深冷空分工艺设计及优化[J]. 化工学报, 2023, 74(7): 2988-2998.
[13]	江锦波, 彭新, 许文烜, 门日秀, 刘畅, 彭旭东. 泵出型螺旋槽油气密封泄漏特性及参数影响研究[J]. 化工学报, 2023, 74(6): 2538-2554.
[14]	孙永尧, 高秋英, 曾文广, 王佳铭, 陈艺飞, 周永哲, 贺高红, 阮雪华. 面向含氮油田伴生气提质利用的膜耦合分离工艺设计优化[J]. 化工学报, 2023, 74(5): 2034-2045.
[15]	刘尚豪, 贾胜坤, 罗祎青, 袁希钢. 基于梯度提升决策树的三组元精馏流程结构最优化[J]. 化工学报, 2023, 74(5): 2075-2087.