Journal of Systems & Management ›› 2025, Vol. 34 ›› Issue (5): 1281-1294.DOI: 10.3969/j.issn.2097-4558.2025.05.007

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Max-NPV Multi-Project Scheduling Optimization with Non-Shared Resource Constraints

HE Hua1,2,3, CAO Fangfang1,2, HE Zhengwen1,2, WANG Nengmin1,2   

  1. 1. School of Management, Xi’an Jiaotong University, Xi’an 710049, China; 2. Key Lab of the Ministry of Education for Process Management and Efficiency Engineering, Xi’an Jiaotong University, Xi’an 710049, China; 3. Modern Business School, Xi’an Vocational and Technical College, Xi’an 710077, China
  • Received:2023-08-29 Revised:2023-12-11 Online:2025-09-28 Published:2025-10-16

非共享资源约束下的净现值最大化多项目调度优化

何华1,2,3,曹芳芳1,2,何正文1,2,王能民1,2   

  1. 1.西安交通大学 管理学院,西安 710049;2.西安交通大学 过程管理与效率工程教育部重点实验室,西安 710049;
    3.西安职业技术学院 现代商学院,西安 710077
  • 基金资助:
    国家自然科学基金资助项目(72371195,71871176,72192830,72192834,72002164,72201147)

Abstract: Taking the maximization of the net present value (NPV) as the objective, this paper investigates the multi-project scheduling problems with non-shared resource constraints. In the problem, the contractor has to allocate resources to individual projects and then under the constraint of the allocated resources, the schedule of each project is arranged independently to maximize its NPV. First, the practical and theoretical backgrounds of the multi-project scheduling problem with non-shared resource constraints are introduced, the research problem is defined, and its research significance is demonstrated. Then, based on the notation definition, the multi-project scheduling optimization model consisting of upper and lower sub-models is developed, and the three basic properties of the problem are proposed. Afterwards, in light of the characteristics of the studied problem, a two-module nested variable neighborhood search heuristic algorithm is designed, where the proposed properties are integrated to enhance the searching efficiency of the algorithm. Finally, in randomly generated standard instances, a large-scale computational experiment is conducted to evaluate the performance of the designed algorithm and analyze the effects of key parameters on the objective function. The findings demonstrate that among the four algorithms compared in the experiment, the variable neighborhood algorithm designed in this paper is the most promising algorithm for the studied problem. The NPV of projects ascends with the increase in the milestone activity number, advanced payment proportion, middle payment proportion, and project deadline while descends with the increase in the cash flow discount rate and resource factor.

Key words: multi-project scheduling, net present value (NPV) maximization, optimization model, variable neighborhood algorithm, non-shared resource

摘要: 本文以净现值最大化为目标,研究非共享资源约束下的多项目调度问题。在该问题中,承包商需先将资源分配给各个独立项目,随后各项目在分配到的资源约束下自主决定进度计划,以实现净现值最大化。首先,阐述非共享资源约束下多项目调度问题的现实背景和理论意义,界定研究问题并论证其价值;其次,基于符号定义,构建由上下层子模型构成的多项目调度优化模型,并提炼问题的3条基本性质;再次,结合问题特征设计双模块嵌套式变邻域搜索启发式算法,将问题性质嵌入算法中以提升搜索效率;最后,通过随机生成的标准算例进行大规模计算实验,评估算法绩效,并分析关键参数对目标函数的影响。研究结论表明:在对比的4种算法中,本文提出的变邻域搜索算法求解效率最优;项目净现值随里程碑活动数量、预付款比例、中间支付比例及项目截止日期的增加而上升,随折现率与资源因子的增大而下降。

关键词: 多项目调度, 净现值最大化, 优化模型, 变邻域算法, 非共享资源

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