计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (2): 250-254.

• 工程与应用 • 上一篇    下一篇

基于改进蚁群算法的项目组合工期-成本优化

白礼彪,白思俊,郭云涛   

  1. 西北工业大学 管理学院,西安 710072
  • 出版日期:2015-01-15 发布日期:2015-01-12

Time-cost optimization of project portfolio based on improved ant colony algorithm

BAI Libiao, BAI Sijun, GUO Yuntao   

  1. School of Management, Northwestern Polytechnical University, Xi’an 710072, China
  • Online:2015-01-15 Published:2015-01-12

摘要: The time-cost trade-off based on the strategic orientation is one of important questions for the multi-project management, which plays a key role in enterprise resources benefit maximization. In order to minimize the value of time-cost trade-off cost and time under the strategic orientation, this paper proposes a mathematical model for the optimization of node selection and order execution in the project portfolio, an improved ant colony solution algorithm, which is on the basis of the adaptive weights, adjusting pheromone variable coefficients and chaotic perturbations has also been designed in this paper to solve the time-cost trade-off problem. The simulation results indicate that the improved algorithm can effectively improve global optimization ability, and much more robust and practical value in solving the time-cost optimization problem of  project portfolio.

关键词: strategic orientation, project portfolio, ant colony algorithm, time-cost optimization

Abstract: The time-cost trade-off based on the strategic orientation is one of important questions for the multi-project management, which plays a key role in enterprise resources benefit maximization. In order to minimize the value of time-cost trade-off cost and time under the strategic orientation, this paper proposes a mathematical model for the optimization of node selection and order execution in the project portfolio, an improved ant colony solution algorithm, which is on the basis of the adaptive weights, adjusting pheromone variable coefficients and chaotic perturbations has also been designed in this paper to solve the time-cost trade-off problem. The simulation results indicate that the improved algorithm can effectively improve global optimization ability, and much more robust and practical value in solving the time-cost optimization problem of  project portfolio.

Key words: strategic orientation, project portfolio, ant colony algorithm, time-cost optimization