基于改进蚁群算法的项目组合工期——成本优化的研究
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摘要
基于企业战略导向的项目组合工期——成本优化问题是企业进行多项目管理时需要解决的重要问题,对企业资源效益最大化发挥起到关键作用,它从本质上属于多目标优化问题。本文将蚁群算法引入项目组合工期——成本优化问题的求解,并针对蚁群算法存在的早熟、停止、局部最优的缺点,提出与混沌结合的改进蚁群算法,引进确定和不确定性搜索规则。实验结果表明,改进的蚁群算法能够有效地提高蚁群算法的全局寻优能力,对工期——成本优化问题的求解能够得出比较好的结果。
The time-cost trade-off based on the strategic orientation is one of the most crucial aspects of enterprise project portfolio planning that plays a key role in enterprise resources benefit maximization,which in fact is a multi-objective optimization problem.A new evolutionary algorithm-ant colony optimization(ACO) algorithm is employed to solve the time-cost trade-off problem.According to the ant colony algorithm existing precocious,stagnation,local optimal shortcomings,adopting certainty and uncertainty search rules and combining with chaos,an improved ant colony algorithm is proposed.Experimental results indicate that join chaos and search rules,the developed ACO can effectively improve global optimization ability,can draw better results in solving time-cost trade-off of project portfolio.
The time-cost trade-off based on the strategic orientation is one of the most crucial aspects of enterprise project portfolio planning that plays a key role in enterprise resources benefit maximization,which in fact is a multi-objective optimization problem.A new evolutionary algorithm-ant colony optimization(ACO) algorithm is employed to solve the time-cost trade-off problem.According to the ant colony algorithm existing precocious,stagnation,local optimal shortcomings,adopting certainty and uncertainty search rules and combining with chaos,an improved ant colony algorithm is proposed.Experimental results indicate that join chaos and search rules,the developed ACO can effectively improve global optimization ability,can draw better results in solving time-cost trade-off of project portfolio.
引文
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[13]Zhang Xiaoli,Chen Xuefeng,He Zhengjia.An ACO-basedalgorithm for parameter optimization of support vector ma-chines[J].Expert Systems with Applications,2010,37(9):6618-6628.
[14]刘道华,李为华,李湘英.多蚁群分级优化的多目标求解方法[J].计算机应用研究,2010,27(10):3705-3717.
[15]沙露,鲍培明,李尼格.基于蚁群系统的聚类算法研究[J].山东大学学报:工学版,2010,40(3):13-18.
[16]Yue Yixiang,Zhou Leishan,Yue Qunxing,et al.Multi-route railroad blocking problem by improved model and antcolony algorithm in real world[J].Computers&IndustrialEngineering,2011,60(1):34-42.
[17]Wang Hua,Xu Hong,Yi Shanwen,et al.A tree-growthbased ant colony algorithm for QoS multicast routing prob-lem[J].Expert Systems with Applications,2011,38(9):11787-11795.
[18]Deng Guang-Feng,Lin Woo-Tsong.Ant colony optimiza-tion-based algorithm for airline crew scheduling problem[J].Expert Systems with Applications,2011,38(5):5787-5793.
[2]Vicente Valls,Francisco Ballestín,Sacramento Quintanil-la.A hybrid genetic algorithm for the resource-constrainedproject scheduling problem[J].European Journal of Oper-ational Research,2008,185(2):495-508.
[3]Hartmann S.A self-adapting genetic algorithm for projectscheduling under resource constraints[J].Naval ResearchLogistics,2002,49(5):433-448.
[4]Jirachai Buddhakulsomsiri,David S Kim.Priority rule-basedheuristic for multi-mode resource-constrained project sched-uling problems with resource vacations and activity splitting[J].European Journal of Operational Research,2007,178(2):374-390.
[5]Kolisch R,Hartmann S.Experimental evaluation of heuris-tics for the resource constrained project scheduling:An up-date[J].European Journal of Operational Research,2006,174(1):23-47.
[6]Yazdani M,Amiri M,Zandieh M.Flexible job-shop schedu-ling with parallel variable neighborhood search algorithm[J].Expert Systems with Applications,2010,37(1):678-687.
[7]Xu Ningxiong,Sally A McKee,Linda K Nozicka,et al.Augmenting priority rule heuristics with justification androllout to solve the resource-constrained project schedulingproblem[J].Computers&Operations Research,2008,35(10):3284-3297.
[8]Kurtulus I,Narola S C.Multi-project scheduling:Analysisof project performance[J].IIE Transactions,1985,17(1):58-66.
[9]Tsai D M,Chiu H N.Two heuristics for scheduling multi-ple projects with constraints[J].Construction Managementand Economies,1996,14(4):325-340.
[10]寿涌毅.多项目资源配置的拉格朗日分解法[J].数量经济技术经济研究,2004(8):98-102.
[11]Daisy X M,Zheng S,Thomas N G,et al.Applying a ge-netic algorithm based multiobjective approach for time-costoptimization[J].Journal of Construction Engineering andManagement,2004,130(2):168-176.
[12]李英民,杨琼,赖明.基于进化策略算法拟合多阻尼比反应谱的地震动仿真[J].世界地震工程,2003,19(2):33-38.
[13]Zhang Xiaoli,Chen Xuefeng,He Zhengjia.An ACO-basedalgorithm for parameter optimization of support vector ma-chines[J].Expert Systems with Applications,2010,37(9):6618-6628.
[14]刘道华,李为华,李湘英.多蚁群分级优化的多目标求解方法[J].计算机应用研究,2010,27(10):3705-3717.
[15]沙露,鲍培明,李尼格.基于蚁群系统的聚类算法研究[J].山东大学学报:工学版,2010,40(3):13-18.
[16]Yue Yixiang,Zhou Leishan,Yue Qunxing,et al.Multi-route railroad blocking problem by improved model and antcolony algorithm in real world[J].Computers&IndustrialEngineering,2011,60(1):34-42.
[17]Wang Hua,Xu Hong,Yi Shanwen,et al.A tree-growthbased ant colony algorithm for QoS multicast routing prob-lem[J].Expert Systems with Applications,2011,38(9):11787-11795.
[18]Deng Guang-Feng,Lin Woo-Tsong.Ant colony optimiza-tion-based algorithm for airline crew scheduling problem[J].Expert Systems with Applications,2011,38(5):5787-5793.
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