基于两层混合遗传算法的IT外包进度风险控制
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摘要
针对IT(information technology)外包项目的两层进度风险控制优化问题,设计了两层混合遗传算法.该算法是在传统遗传算法中引入模拟退火和自适应机制,并结合优化问题的两层特点而设计的,能够克服传统遗传算法易于早熟、局部搜索能力较差的弱点.在算例分析中,首先分析了两层数学模型在IT外包项目进度风险控制中的管理意义,进而将两层混合遗传算法的仿真结果与两层粒子群优化算法和传统遗传算法的仿真结果进行比较,验证了改进算法的效率和有效性.
Focusing on the optimization problem of schedule risk control in information technology(IT)outsourcing project,a two-level hybrid genetic algorithm(TLHGA) is proposed.The TLHGA incorporates simulated annealing,adaptive mechanism and the two-level feature of optimization problem to improve the traditional genetic algorithm(TGA),which could overcome the shortcomings of TGA such as early mature and weak local searching ability.In the experimental analyses,the management meanings of the two-level mathematical model in IT outsourcing schedule risk control is analyzed.Next,the simulation results of TLHGA are compared with the TGA and two-level particle swarm optimization algorithm,which verifies the rationality and effectiveness of the improved algorithm.
Focusing on the optimization problem of schedule risk control in information technology(IT)outsourcing project,a two-level hybrid genetic algorithm(TLHGA) is proposed.The TLHGA incorporates simulated annealing,adaptive mechanism and the two-level feature of optimization problem to improve the traditional genetic algorithm(TGA),which could overcome the shortcomings of TGA such as early mature and weak local searching ability.In the experimental analyses,the management meanings of the two-level mathematical model in IT outsourcing schedule risk control is analyzed.Next,the simulation results of TLHGA are compared with the TGA and two-level particle swarm optimization algorithm,which verifies the rationality and effectiveness of the improved algorithm.
引文
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[2]曹萍,陈福集,张剑.基于进度的软件外包项目风险优化控制决策[J].武汉大学学报(工学版),2012,45(3):385-388.(Cao Ping,Chen Fu-ji,Zhang Jian.Risk optimization control decision-making of software outsourcing project based on schedule[J].Engineering Journal of Wuhan University,2012,45(3):385-388.)
[3]Münch J,Heidrich J.Software project control centers:concepts and approaches[J].Journal of Systems&Software,2004,70(1):3-19.
[4]Yassine A A,Mostafa O,Browning T R.Scheduling multiple,resource-constrained,iterative,product development projects with genetic algorithms[J].Computers&Industrial Engineering,2017,107:39-56.
[5]Boehm B.Anchoring the software process[J].IEEE Software,1996,13(4):73-82.
[6]周方明,张明媛,袁永博.基于PCA-GA-BP的工程项目工期风险预测研究[J].工程管理学报,2011,25(5):534-538.(Zhou Fang-ming,Zhang Ming-yuan,Yuan Yong-bo.Risk of project time based on PCA-GA-BP[J].Journal of Engineering Management,2011,25(5):534-538.)
[7]Dao S D,Abhary K,Marian R.A bibliometric analysis of genetic algorithms throughout the history[J].Computers&Industrial Engineering,2017,110:395-403.