基于两层混合遗传算法的IT外包进度风险控制  

IT Outsourcing Schedule Risk Control Based on Two-Level Hybrid Genetic Algorithm

作　　者：王雷震[1,2] 朱锦文 卢福强 汪定伟[1] WANG Lei-zhen;ZHU Jin-wen;LU Fu-qiang;WANG Ding-wei(School of Information Science&Engineering,Northeastern University,Shenyang 110819,China;School of Management,Northeastern University at Qinhuangdao,Qinhuangdao 066004,China)

机构地区：[1]东北大学信息科学与工程学院,辽宁沈阳110819 [2]东北大学秦皇岛分校管理学院,河北秦皇岛066004

出　　处：《东北大学学报（自然科学版）》2019年第2期164-168,179,共6页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(71401027);河北省自然科学基金资助项目(G2016501086);中央高校基本科研业务费专项资金资助项目(N172304016);河北省高等学校科学技术研究重点项目(ZD2016202)

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.

关 键 词：IT外包 进度风险 混合算法 遗传算法 模拟退火 

分 类 号：N945[自然科学总论—系统科学]