数学优化
计算机科学
文件夹
项目组合管理
作业车间调度
利润(经济学)
进化算法
调度(生产过程)
运筹学
人工智能
项目管理
地铁列车时刻表
数学
工程类
经济
微观经济学
系统工程
金融经济学
操作系统
作者
Yongyi Shou,Wenwen Xiang,Ying Li,Wenxi Yao
摘要
A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.
科研通智能强力驱动
Strongly Powered by AbleSci AI