微粒群算法在工程项目集成管理优化问题中的研究与应用
|
摘要
工程项目由若干工作组成,在项目的管理过程中,项目的主要目标——工期、成本、质量密切相关,任何一方发生变化都将会引起其它方面发生相应的变化,并直接或间接地对工程项目产生影响,因此对项目的各项工作进行集成管理优化显得尤为重要。
微粒群算法是一种进化计算技术,源于对鸟群捕食行为的研究。与其他优化方法相比,微粒群优化算法的优势在于容易实现同时又有深刻的智能背景,既适合科学研究,又特别适合工程应用。
该论文查询了近20年的国内外相关文献,以系统科学理论为基础,从集成管理的概念出发,首先,提出了工程项目集成管理优化的基本理论与方法,建立了工程项目集成管理优化的概念模型,该模型的求解属于国际上公认的NP—hard难题之一,针对此难题提出了利用基于优先权的编码技术和拓扑排序知识把概念模型转化为数学模型,使得模型的求解成为可能,同时也避开了模型求解时惩罚算子繁琐的设计问题。其次,在研究工程质量的量化方程时,运用柯布—道格拉斯回归模型描述工程质量与工程工期、成本间的定量关系。接着,引入了微粒群算法,定义微粒的含义,使用线性加权方法构造微粒适应值函数,解决了多目标间比较时产生偏序问题的难题,从而实现了多目标优化模型向单目标优化模型的转化。而后,提出同时具有惯性权重和限定因子参数的新版本微粒群算法,在论文附件中编制其matlab求解源程序,运用在以管道水平定向钻穿越工程为工程实例的集成管理优化模型中;经过反复地实验,给出了适合该工程实例的参数组合,微粒群算法程序在求解过程表现出了高效的搜索能力,获得了满意的优化结果。最后,着重讨论了在微粒群算法参数设计中微粒个体意识与集体意识的比较分析和微粒群种群规模与协同搜索能力的关系;在工程项目参数变化分析中,探索性地讨论了资源限量变化对集成管理优化最优结果的影响和微粒适应值函数中权重变化的设计以及集成管理优化模型的逆问题求解方法等难题。
该论文有图13幅,表3个,参考文献65篇。
Project consists of several works. In the process of a project management, the relationships among project three significant goals those are time cost and quality are high connected. Once any one among those goals was changed, it will have great influences on other one directly or indirectly. Therefore, it is very significant to manage all the works as integration after optimizing.
Particle swarm optimization is evolutionary computation technique. It came of the research on bird flock preying behavior. Compared with other optimization algorithms, particle swarm optimization superiorities consist in achieved easily and having profound intellect background. Particle swarm optimization was not only suit for scientific research but also suit for project application.
After querying recent 20 years related reference in and out of china, based on system science theory, started with the conception of integration management, Firstly, this thesis advanced basic theory and method of project integration management optimization, setup conceptive optimization model of project integration management which belongs to international legalized NP-hard problem, and then transformed conceptive model into mathematics model by using priority-based encoding and topological sort technique so that made solving the model possible and avoided designing the complex penalty function. Secondly, when it came to the research of project quality equation, this thesis described the quantity relationship among project quality time cost by using Cobb-Dauglas model. Thirdly, this thesis imported particle swarm optimization and defined the particle to solve partial order problem when compared particle fitness value by constructed particle fitness function in linear weight method. It achieved that multi-object model transformed into single-object model successfully. Fourthly, this thesis brought up a new version particle swarm optimization which both had inertia weight and constriction factor parameters. The author wrote matlab procedure in appendix and applied it in integration management optimization problem that took pipeline horizontal direction drilling project for example. After time and time experimenting, the author found out suit parameters combination for given instance project. Particle swarm optimization performed high efficient search capability in solving process and gained approving optimum results. In the end, this thesis put stress on analyzing particle individual consciousness versus collective consciousness and the relationship between particle swarm size and ability of co-operation searching in particle swarm optimization parameter design. In the process of analyzing project parameters change, this thesis discussed the influences of constrained resource quantity on integration management optimization result and linear weight coefficient selection in particle fitness function design. The author also suggested a method for the inverse model of integration management optimization problem.
There are 13 graphs 3 tables and 65 references in this thesis.
微粒群算法是一种进化计算技术,源于对鸟群捕食行为的研究。与其他优化方法相比,微粒群优化算法的优势在于容易实现同时又有深刻的智能背景,既适合科学研究,又特别适合工程应用。
该论文查询了近20年的国内外相关文献,以系统科学理论为基础,从集成管理的概念出发,首先,提出了工程项目集成管理优化的基本理论与方法,建立了工程项目集成管理优化的概念模型,该模型的求解属于国际上公认的NP—hard难题之一,针对此难题提出了利用基于优先权的编码技术和拓扑排序知识把概念模型转化为数学模型,使得模型的求解成为可能,同时也避开了模型求解时惩罚算子繁琐的设计问题。其次,在研究工程质量的量化方程时,运用柯布—道格拉斯回归模型描述工程质量与工程工期、成本间的定量关系。接着,引入了微粒群算法,定义微粒的含义,使用线性加权方法构造微粒适应值函数,解决了多目标间比较时产生偏序问题的难题,从而实现了多目标优化模型向单目标优化模型的转化。而后,提出同时具有惯性权重和限定因子参数的新版本微粒群算法,在论文附件中编制其matlab求解源程序,运用在以管道水平定向钻穿越工程为工程实例的集成管理优化模型中;经过反复地实验,给出了适合该工程实例的参数组合,微粒群算法程序在求解过程表现出了高效的搜索能力,获得了满意的优化结果。最后,着重讨论了在微粒群算法参数设计中微粒个体意识与集体意识的比较分析和微粒群种群规模与协同搜索能力的关系;在工程项目参数变化分析中,探索性地讨论了资源限量变化对集成管理优化最优结果的影响和微粒适应值函数中权重变化的设计以及集成管理优化模型的逆问题求解方法等难题。
该论文有图13幅,表3个,参考文献65篇。
Project consists of several works. In the process of a project management, the relationships among project three significant goals those are time cost and quality are high connected. Once any one among those goals was changed, it will have great influences on other one directly or indirectly. Therefore, it is very significant to manage all the works as integration after optimizing.
Particle swarm optimization is evolutionary computation technique. It came of the research on bird flock preying behavior. Compared with other optimization algorithms, particle swarm optimization superiorities consist in achieved easily and having profound intellect background. Particle swarm optimization was not only suit for scientific research but also suit for project application.
After querying recent 20 years related reference in and out of china, based on system science theory, started with the conception of integration management, Firstly, this thesis advanced basic theory and method of project integration management optimization, setup conceptive optimization model of project integration management which belongs to international legalized NP-hard problem, and then transformed conceptive model into mathematics model by using priority-based encoding and topological sort technique so that made solving the model possible and avoided designing the complex penalty function. Secondly, when it came to the research of project quality equation, this thesis described the quantity relationship among project quality time cost by using Cobb-Dauglas model. Thirdly, this thesis imported particle swarm optimization and defined the particle to solve partial order problem when compared particle fitness value by constructed particle fitness function in linear weight method. It achieved that multi-object model transformed into single-object model successfully. Fourthly, this thesis brought up a new version particle swarm optimization which both had inertia weight and constriction factor parameters. The author wrote matlab procedure in appendix and applied it in integration management optimization problem that took pipeline horizontal direction drilling project for example. After time and time experimenting, the author found out suit parameters combination for given instance project. Particle swarm optimization performed high efficient search capability in solving process and gained approving optimum results. In the end, this thesis put stress on analyzing particle individual consciousness versus collective consciousness and the relationship between particle swarm size and ability of co-operation searching in particle swarm optimization parameter design. In the process of analyzing project parameters change, this thesis discussed the influences of constrained resource quantity on integration management optimization result and linear weight coefficient selection in particle fitness function design. The author also suggested a method for the inverse model of integration management optimization problem.
There are 13 graphs 3 tables and 65 references in this thesis.
引文
[1]邱菀华,沈建明,杨爱华.现代项目管理导论[M].北京:机械工业出版社,2002:6-9.
[2]马国丰,尤建新,杜学美.项目进度的制约因素管理[M].北京:清华大学,2007:1-13.
[3]蔚林巍.项目管理的最新进展及应用[J],管理工程学报,2000:Vo1.14, No.3, 65-69.
[4]汪应洛,王能民.我国工程管理学科现状及发展[J].中国工程科学,2006:Vo1.18, No.13, 12-17.
[5]郭晓霞.建设工程项目集成管理系统的研究[D],西安建筑科技大学硕士学位论文,2005.6.
[6]国际项目管理发展史,综合应用yhua@mypm.net.
[7] P D.Rwelamila et al.Total Systems Intervention:an Integrated Approach to Time,Cost and Control [J]. Transactions 1998.
[8]戚安邦.挣值分析中项目完工成本预测方法的问题与出路[J].预测,2004:56-60.
[9]路涛.建设项目实施阶段集成管理的理论与实践研究[D].华北电力大学硕士学位论文,2005:1-3.
[10] McKim R, Hegazy T, Aualla M. Project performance control in reconstruction projects[J].Journal of Construction Engineering and Management, 2000, 126 (2):137-141.
[11] Rwelamila P D, et al. Total systems intervention: An integrated approach to time, cost and quality management[J]. Construction Management and Economic, 1995,13:235-241.
[12] A. R. Burgess, J. B. Killebrew. Variation in Activity Level on a Cyclic Arrow Diagram[J]. Journal of Industrial Engineering. Feb. 1982: 76-83.
[13] E. W. Davis, G. E. Heidorn. An Algorithm for Optimal Scheduling Under Multiple Resource Constraints[J]. Management Science. Dec. 1971: 803-813.
[14] E. Padilla, R. Carr. Resource Strategies for Uyname Project Management[J]. Journal of Construction Engineering and Management. Feb. 1991: 279-293.
[15] L. Natale , F. Savi.Monte Carlo analysis of probability of inundation of Rome[J]. Environmental Modelling & Software 22 (2007): 1409-1416
[16] Rainer Kolisch, Soonke Hartmann. Experimental investigation of heuristics for resource constrained project scheduling: An update[J].European Journal of Operational Research 174 (2006): 23–37.
[17] Lawrence S R, Morton T E. Resource-constrained Multi-project Scheduling with Tardy Cost: Comparing Myopic, Bottleneck, and Resource Pricing Heuristics[J]. European Journal ofOperational Research, 1993, 64: 168-187.
[18] Hindelang T J, Muth J F. A Dynamic Programming Algorithm for Decision CPM Networks[J]. Operation Research, 1979, 27: 225-241.
[19] Demeulemeester E L, De Reyck B, Foubert B, et al. New Computational Results on The Discrete Time/Cost Trade-off Problem in Project Networks[J]. Journal of the Operational Research Society, 1998,49: 1153-1163.
[20] Alena Labodova′. Implementing integrated management systems using a risk analysis based approach[J] . Journal of Cleaner Production 12 (2004) 571–580.
[21]丁士昭.国际工程项目管理模式的探讨[J].土木工程学报,2002(1):42一47.
[22]王延树,成虎.大型施工项目的集成管理[J].东南大学学报,2000(7):1-5.
[23]李瑞涵.工程项目集成化管理理论与创新研究[D].天津大学博士学位论文,2002.
[24]何曙光,齐二石,汪洋等.面向工程建设的现代集成管理系统研究[J].计算机集成制造系统,2002(4) :330-332.
[25]李树海.在项目管理中如何协调质量、进度、成本的关系[J].内蒙古科技与经济,2003 (3):66- 67.
[26]李红兵.建设项目集成化管理理论与方法研究[D].武汉理工大学博士学位论文,2004.
[27]赵丽坤.工程项目综合集成化管理模式研究[D].河北工业大学硕士学位论文,2004.
[28]沈小平,马士华.基于人机网络一体化的综合集成管理支持系统研究[J].系统工程理论与实践,2006年第8期:86-90.
[29]李蔚,刘小群.工程项目集成管理及其软件系统[J].建筑经济,2004年8月:34-37.
[30]王乾坤.集成管理原理分析与运行探索[J].武汉大学学报(哲学社会科学版),2006年5月:255-259.
[31]庄越,王建华.面向产品创新的集成管理内生机理研究[J].科技进步及对策,2005年5月:57-58.
[32]姜继娇,杨乃定.基于集成管理理论的企业危机预警机制研究[J].科研管理,第25卷第5期:81-84.
[33]刘士新,王梦光,聂义勇.多执行模式资源受限工程调度问题的优化算法[J].系统工程学报,2001年第16卷第1期:55-60.
[34]王会玲,刘民,吴澄启.启发式算法在网络计划多资源平衡中的应用[J].计算机工程与应用,2003.14:226-228.
[35]赵建国,王雪青.蒙特卡洛模拟在随机网络中的工程应用[J].内蒙古工业大学学报,2004,Vol.23 No.23: 236-240.
[36]骆刚,刘尔烈,王健.遗传算法在网络计划资源优化中的应用[J].天津大学学报.第37卷第2期2004年2月: 179-183.
[37]郭研,宁宣熙.利用遗传算法求解多项目资源平衡问题[J].系统工程理论与实践, 2005年10月:78-82.
[38]王巍,赵国杰.粒子群优化在资源受限工程调度问题中的应用[J].哈尔滨工业大学学报, 2007年4月,第39卷第4期:669-672.
[39]腾居特,顾幸生.小生境微粒群优化算法[J].华东理工大学学报(自然科学版),2007年2月,第33卷第1期:133-136.
[40]刘尔烈,张艳海.建筑施工项目进度、成本和质量目标的综合优化[J].天津理工学院学报,2001年6月,第17卷第2期:90-93.
[41]蔚林巍,徐今勇.优化项目管理[J].企业管理,2003年12月:30-33.
[42]刘士新.项目优化调度理论与方法[M].北京:机械工业出版社,2007:88-100.
[43]丛培经,张书行编著.工程项目管理[M].北京:中国建筑工业出版社,1997年6月.
[44]戴汝为等.智能系统的综合集成[M].杭州:浙江科技出版社,1995.
[45]龚建桥等.科技企业集成管理研究论纲[J].科技管理,1996(3).
[46]刘晓强.集成论初探[J].中国软科学,1997(10): 103.
[47]李宝山,刘志伟.集成管理—高科技时代的管理创新[M].北京:中国人民大学出版社,1998:34-35.
[48]海峰.企业管理集成的理论和方法(D).武汉理工大学,2001.
[49]刘尔烈,蔡耿谦.工程项目集成化管理[J].港工技术,2001(4):19-21.
[50]李子奈,潘文清.计量经济学(第2版)[M].北京:高等教育出版社,2005:217-241.
[51] Cheng, R. and M. Gen, Evolution program for Resource constrained project Scheduling problem, in Fogel[197], pp. 736-741.
[52] Cheng, R. and M. Gen, Resource constrained project Scheduling problem using genetic algorithms, International Journal of Intelligent Automation and Soft Computing,vol. 3, no. 3, 1997: pp. 73-286.
[53] Kennedy J, Eberhart R. Particle swarn optimization[A]. Pro IEEE Int Conf on Neural Networks[C]. Perth, 1995. 1942-1948.
[54] Eberhart R, Kennedy J. A new optimizer using particle swarm theory[A]. Proc 6th Int Symposium on Micro Machine and Human Science[C]. Nagoya, 1995. 39-43.
[55] Wilson E O. Sociobiology: The New Synthesis[M]. MA: Belknap Press, 1975.
[56] Shi Yuhui, Eberhart R. A modified particle swarm optimizer[A].. Anchorage,1998. 69-73.
[57]金新磊:基于PSO的多目标优化算法研究及应用[D],浙江大学博士学位论文,2006年07月.
[58] Kennedy J. The particle swarm: Social adaptation of knowledge[A]. Pro IEEE Pro IEEE Int Conf on Evolutionary Computation[C]. Indiamapolis, 1997. 303-308.
[59] Thorndike E L. Animal Intelligence: Empirical Studies[M]. New York: MacMillan, 1911.
[60] Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory[M]. New Jersey: Prentice Hall, 1986.
[61] M. Clerc, J. Kennedy, The particle swarm explosion, stability, and convergence in a multidimensional complex space, IEEE Transaction on Evolutionary Computation 6 (2002) 58–73.
[62] F.Vanden Bergh,An analysis of particle swarm optimizers.PHD thesis[D].University of Pretoria,Pretoria.South Africa, 2002.
[63]刘荣哲.水平定向钻穿越河流解卡技术的探讨[J].石油工程建设,2005年4月第31卷第2期:51-52
[64]蒲世东.定向钻穿越施工危害评价与风险削减[J].油气田地面工程,2006年5月第25卷第5期:52-53
[65]李强,张静,张耀坦.蒙特卡洛仿真技术在工程进度计划中的应用[J].长江大学学报(自然科学版),2007年第2期:62-65
[2]马国丰,尤建新,杜学美.项目进度的制约因素管理[M].北京:清华大学,2007:1-13.
[3]蔚林巍.项目管理的最新进展及应用[J],管理工程学报,2000:Vo1.14, No.3, 65-69.
[4]汪应洛,王能民.我国工程管理学科现状及发展[J].中国工程科学,2006:Vo1.18, No.13, 12-17.
[5]郭晓霞.建设工程项目集成管理系统的研究[D],西安建筑科技大学硕士学位论文,2005.6.
[6]国际项目管理发展史,综合应用yhua@mypm.net.
[7] P D.Rwelamila et al.Total Systems Intervention:an Integrated Approach to Time,Cost and Control [J]. Transactions 1998.
[8]戚安邦.挣值分析中项目完工成本预测方法的问题与出路[J].预测,2004:56-60.
[9]路涛.建设项目实施阶段集成管理的理论与实践研究[D].华北电力大学硕士学位论文,2005:1-3.
[10] McKim R, Hegazy T, Aualla M. Project performance control in reconstruction projects[J].Journal of Construction Engineering and Management, 2000, 126 (2):137-141.
[11] Rwelamila P D, et al. Total systems intervention: An integrated approach to time, cost and quality management[J]. Construction Management and Economic, 1995,13:235-241.
[12] A. R. Burgess, J. B. Killebrew. Variation in Activity Level on a Cyclic Arrow Diagram[J]. Journal of Industrial Engineering. Feb. 1982: 76-83.
[13] E. W. Davis, G. E. Heidorn. An Algorithm for Optimal Scheduling Under Multiple Resource Constraints[J]. Management Science. Dec. 1971: 803-813.
[14] E. Padilla, R. Carr. Resource Strategies for Uyname Project Management[J]. Journal of Construction Engineering and Management. Feb. 1991: 279-293.
[15] L. Natale , F. Savi.Monte Carlo analysis of probability of inundation of Rome[J]. Environmental Modelling & Software 22 (2007): 1409-1416
[16] Rainer Kolisch, Soonke Hartmann. Experimental investigation of heuristics for resource constrained project scheduling: An update[J].European Journal of Operational Research 174 (2006): 23–37.
[17] Lawrence S R, Morton T E. Resource-constrained Multi-project Scheduling with Tardy Cost: Comparing Myopic, Bottleneck, and Resource Pricing Heuristics[J]. European Journal ofOperational Research, 1993, 64: 168-187.
[18] Hindelang T J, Muth J F. A Dynamic Programming Algorithm for Decision CPM Networks[J]. Operation Research, 1979, 27: 225-241.
[19] Demeulemeester E L, De Reyck B, Foubert B, et al. New Computational Results on The Discrete Time/Cost Trade-off Problem in Project Networks[J]. Journal of the Operational Research Society, 1998,49: 1153-1163.
[20] Alena Labodova′. Implementing integrated management systems using a risk analysis based approach[J] . Journal of Cleaner Production 12 (2004) 571–580.
[21]丁士昭.国际工程项目管理模式的探讨[J].土木工程学报,2002(1):42一47.
[22]王延树,成虎.大型施工项目的集成管理[J].东南大学学报,2000(7):1-5.
[23]李瑞涵.工程项目集成化管理理论与创新研究[D].天津大学博士学位论文,2002.
[24]何曙光,齐二石,汪洋等.面向工程建设的现代集成管理系统研究[J].计算机集成制造系统,2002(4) :330-332.
[25]李树海.在项目管理中如何协调质量、进度、成本的关系[J].内蒙古科技与经济,2003 (3):66- 67.
[26]李红兵.建设项目集成化管理理论与方法研究[D].武汉理工大学博士学位论文,2004.
[27]赵丽坤.工程项目综合集成化管理模式研究[D].河北工业大学硕士学位论文,2004.
[28]沈小平,马士华.基于人机网络一体化的综合集成管理支持系统研究[J].系统工程理论与实践,2006年第8期:86-90.
[29]李蔚,刘小群.工程项目集成管理及其软件系统[J].建筑经济,2004年8月:34-37.
[30]王乾坤.集成管理原理分析与运行探索[J].武汉大学学报(哲学社会科学版),2006年5月:255-259.
[31]庄越,王建华.面向产品创新的集成管理内生机理研究[J].科技进步及对策,2005年5月:57-58.
[32]姜继娇,杨乃定.基于集成管理理论的企业危机预警机制研究[J].科研管理,第25卷第5期:81-84.
[33]刘士新,王梦光,聂义勇.多执行模式资源受限工程调度问题的优化算法[J].系统工程学报,2001年第16卷第1期:55-60.
[34]王会玲,刘民,吴澄启.启发式算法在网络计划多资源平衡中的应用[J].计算机工程与应用,2003.14:226-228.
[35]赵建国,王雪青.蒙特卡洛模拟在随机网络中的工程应用[J].内蒙古工业大学学报,2004,Vol.23 No.23: 236-240.
[36]骆刚,刘尔烈,王健.遗传算法在网络计划资源优化中的应用[J].天津大学学报.第37卷第2期2004年2月: 179-183.
[37]郭研,宁宣熙.利用遗传算法求解多项目资源平衡问题[J].系统工程理论与实践, 2005年10月:78-82.
[38]王巍,赵国杰.粒子群优化在资源受限工程调度问题中的应用[J].哈尔滨工业大学学报, 2007年4月,第39卷第4期:669-672.
[39]腾居特,顾幸生.小生境微粒群优化算法[J].华东理工大学学报(自然科学版),2007年2月,第33卷第1期:133-136.
[40]刘尔烈,张艳海.建筑施工项目进度、成本和质量目标的综合优化[J].天津理工学院学报,2001年6月,第17卷第2期:90-93.
[41]蔚林巍,徐今勇.优化项目管理[J].企业管理,2003年12月:30-33.
[42]刘士新.项目优化调度理论与方法[M].北京:机械工业出版社,2007:88-100.
[43]丛培经,张书行编著.工程项目管理[M].北京:中国建筑工业出版社,1997年6月.
[44]戴汝为等.智能系统的综合集成[M].杭州:浙江科技出版社,1995.
[45]龚建桥等.科技企业集成管理研究论纲[J].科技管理,1996(3).
[46]刘晓强.集成论初探[J].中国软科学,1997(10): 103.
[47]李宝山,刘志伟.集成管理—高科技时代的管理创新[M].北京:中国人民大学出版社,1998:34-35.
[48]海峰.企业管理集成的理论和方法(D).武汉理工大学,2001.
[49]刘尔烈,蔡耿谦.工程项目集成化管理[J].港工技术,2001(4):19-21.
[50]李子奈,潘文清.计量经济学(第2版)[M].北京:高等教育出版社,2005:217-241.
[51] Cheng, R. and M. Gen, Evolution program for Resource constrained project Scheduling problem, in Fogel[197], pp. 736-741.
[52] Cheng, R. and M. Gen, Resource constrained project Scheduling problem using genetic algorithms, International Journal of Intelligent Automation and Soft Computing,vol. 3, no. 3, 1997: pp. 73-286.
[53] Kennedy J, Eberhart R. Particle swarn optimization[A]. Pro IEEE Int Conf on Neural Networks[C]. Perth, 1995. 1942-1948.
[54] Eberhart R, Kennedy J. A new optimizer using particle swarm theory[A]. Proc 6th Int Symposium on Micro Machine and Human Science[C]. Nagoya, 1995. 39-43.
[55] Wilson E O. Sociobiology: The New Synthesis[M]. MA: Belknap Press, 1975.
[56] Shi Yuhui, Eberhart R. A modified particle swarm optimizer[A].. Anchorage,1998. 69-73.
[57]金新磊:基于PSO的多目标优化算法研究及应用[D],浙江大学博士学位论文,2006年07月.
[58] Kennedy J. The particle swarm: Social adaptation of knowledge[A]. Pro IEEE Pro IEEE Int Conf on Evolutionary Computation[C]. Indiamapolis, 1997. 303-308.
[59] Thorndike E L. Animal Intelligence: Empirical Studies[M]. New York: MacMillan, 1911.
[60] Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory[M]. New Jersey: Prentice Hall, 1986.
[61] M. Clerc, J. Kennedy, The particle swarm explosion, stability, and convergence in a multidimensional complex space, IEEE Transaction on Evolutionary Computation 6 (2002) 58–73.
[62] F.Vanden Bergh,An analysis of particle swarm optimizers.PHD thesis[D].University of Pretoria,Pretoria.South Africa, 2002.
[63]刘荣哲.水平定向钻穿越河流解卡技术的探讨[J].石油工程建设,2005年4月第31卷第2期:51-52
[64]蒲世东.定向钻穿越施工危害评价与风险削减[J].油气田地面工程,2006年5月第25卷第5期:52-53
[65]李强,张静,张耀坦.蒙特卡洛仿真技术在工程进度计划中的应用[J].长江大学学报(自然科学版),2007年第2期:62-65