基于改进蚁群算法的项目组合工期——成本优化的研究

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.