工业工程 ›› 2014, Vol. 17 ›› Issue (1): 37-43.

• 实践与应用 • 上一篇    下一篇

项目员工加班调度多目标优化模型与算法

  

  1. 1.北京航空航天大学 经济管理学院,北京 100191; 2.石家庄铁道大学 经济管理学院,河北 石家庄 050043
  • 出版日期:2014-02-28 发布日期:2014-03-14
  • 作者简介:李明(1975-),男,河南省人,副教授,博士研究生,主要研究方向为项目管理.
  • 基金资助:

    国家自然科学基金资助项目(712710191)

Multi-objective Optimization Model and Algorithm on Overtime Scheduling in Project

  1. 1.School of Economics and Management, Beihang University, Beijing 100191, China; 
    2.School of Economics and Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
  • Online:2014-02-28 Published:2014-03-14

摘要: 为最小化加班对项目工期、人力资源成本和总加班时间的影响,建立了项目员工加班调度多目标优化模型。首先,采用初始化模块生成各活动的可行加班方案;然后,使用调度模块计算确定每一种调度方案的项目工期、人力资源成本和总加班时间;最后,采用并列选择遗传算法得到多目标Pareto解集。研究结果表明,使用该模型能够有效的确定出工期短、人力资源成本低和总加班时间少的员工加班调度方案集合,从而为项目管理者提供有力的加班调度决策支持。

关键词: 加班调度, 多目标优化, 遗传算法

Abstract: To minimize the negative impact of overtime working, a new multiobjective optimization model is put forward and the corresponding solution algorithm is proposed. First, a feasible overtime work set is generated for each activity in the initialization stage. Then, the project duration, human resource cost, and total overtime hours of each scheduling plan are calculated by using the scheduling module. Finally, with a multiobjective genetic algorithm module, a Pareto multiobjective solution set is obtained. In addition, this algorithm is used in a case study, and the results show that the model is good in practicability, and can provide decision support for project managers on overtime scheduling.

Key words: overtime scheduling, multiobjective optimization, genetic algorithm