摘要
针对传统项目调度中多以优化工期而忽略财务目标的问题,提出了求解现金流平衡下最大化净现值项目调度问题(Max-NPV)的人工蜂群算法(ABC)。在Max-NPV模型中增加一个支付决策变量以满足项目承包方依据资金链状况获取支付的需求,设计两组向量表示位置编码,采用随机邻域搜索机制进行不同调度的生成。实验结果得到的项目收益对比参考数据更加接近最优解,求解过程示意图显示了ABC算法全局寻优特点。ABC算法能够有效求解项目调度等组合优化问题,进一步拓展算法的应用领域。
In view of that the traditional project scheduling mostly optimizes duration and ignores the goal of finance, the Artificial Bee Colony （ABC） algorithm for maximizing the net present value of project scheduling problem under the balance of cash flow （Max-NPV） was proposed. In Max-NPV model a payment decision variable was added to satisfy the project contractor＇s needs of getting the payment according to capital chain condition, two sets of vectors were designed to indicate the location code, different scheduling was generated by using random neighborhood search mechanism. The project revenue obtained by experimental results is more close to the optimal solution compared to reference data, the global optimization characteristic of ABC algorithm was shown by the solution process diagram. The ABC algorithm can effectively solve the project scheduling and combinatorial optimization problem, further expand the application field of the algorithm.
出处
《计算机应用》
CSCD
北大核心
2016年第A02期85-88,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(71471016)
关键词
现金流平衡
净现值
人工蜂群算法
双代号网络
项目调度
cash flow balance
Net Present Value （NPV）
artificial bee colony
activity on arc network
project scheduling
