一种策略层项目计划的双目标优化方法

doi:10.16381/j.cnki.issn1003-207x.2019.0258

摘要/Abstract

摘要： 针对产品开发项目管理的实际情况，对策略层计划优化方法进行研究。以工作包的工作量估算为基础，以资源投入水平和工期最小化为目标，考虑各种约束条件，提出一种策略层项目计划问题的混合整数规划问题模型。以非支配遗传算法NSGA-II为基础框架，设计了一种改进的双目标遗传算法。该算法针对问题的特点，提出了基于资源平滑的解码算法。参考NSGA-III的关键特征，对拥挤密度计算方法进行改进。通过企业实际项目案例，验证了算法的性能和所提出的策略层项目计划方法的有效性。

关键词: 项目管理, 策略层计划, 多目标优化, 遗传算法

Abstract: In general project management practice, the expected objectives and resource allocation are delivered from the project plans at the tactical level to the plans at execution level. However, the optimization approaches of tactical project planning are scarce while there are lots of existing approaches focusing on the project scheduling problems at the execution level. In this paper, a new optimization method of project planning at strategic level is studied in view of the actual situation of product development project management. Based on the workload estimation of the work package, a mixed integer programming model for the tactical project planning problem is addressed, with the dual objectives of minimizing the resource level and the make-span of multiple projects under various constraints such as resource, precedence relationship among work packages, etc. An improved bi-objective genetic algorithm is developed in the framework of the fast non-dominated sorting genetic algorithm (NSGA-Ⅱ). There are two significant improvements based on the basic NSGA-Ⅱ in the algorithm. Firstly, aiming at the characteristics of the problem, a decoding algorithm based on resource smoothing is designed. Secondly, referring to the key feature of NSGA-Ⅲ, the calculation method of congestion density is improved and a new calculation method is proposed. The performance of the algorithm is verified by comparision of the improved algorithm with the basic NSGA-Ⅱ for solving a real project case. The effectiveness of the appraoch proposed in this paper is shown and illustrated based on the analysis of the results calculated by the presented algorithm,since it can provide the project decision maker with more comprehensive support.The research will extend the research of project planning and scheduling to the macro level of project management.

Key words: project management, tactical project planning, multi-objective optimization, genetic algorithm

中图分类号:

F237

彭武良, 马小菁. 一种策略层项目计划的双目标优化方法[J]. 中国管理科学, 2021, 29(2): 69-77.

PENG Wu-liang, MA Xiao-jing. A Bi-objective Optimization Method for Tactical Project Planning[J]. Chinese Journal of Management Science, 2021, 29(2): 69-77.

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