摘要
复杂不确定环境下,制定一个具有较强抗干扰能力的基准进度计划非常必要。本文研究了活动工期不确定环境下考虑活动可拆分的项目资源鲁棒性调度优化问题,旨在考虑活动可拆分,探究在活动优先关系约束、项目截止日期约束、活动拆分约束、资源流约束等条件下如何进行活动拆分决策并合理地安排各个项目活动/活动分段间的资源调配方案和时间缓冲添加策略,以制定鲁棒性最大化的基准进度计划。本文创新点如下:1)在项目资源鲁棒性调度优化问题中考虑活动可拆分,定义了资源流网络下活动自由时差的计算方法,提出了一种新的活动可拆分情形下进度计划鲁棒性的衡量方式,进而构建得到了考虑活动可拆分的项目资源鲁棒性调度优化模型;2)分析证明了问题模型的强NP-hard属性以及非线性属性,并在此基础上开发了一种内嵌资源调度安排的遗传算法进行问题求解;3)选取一个典型的实际案例对研究问题进行说明,直观展示了活动拆分执行对进度计划鲁棒性提升的重要价值,揭示了鲁棒性调度计划中资源调度方案的重要性,得到了活动拆分执行会增加项目内部资源转移次数的结论。
In practice, faced with the complex and uncertain environment, it is really necessary for project managers to construct a robust resource allocation schedule with a strong anti-interference ability. At the stage of schedule generation, activities may be not divided into the smallest units, so project managers can choose to further split activities into subactivities under specific constraints. When taking activity splitting into account, on the one hand, it will be more flexible for activity scheduling;on the other hand, it will be more complex for resource allocation between the subactivities.In this paper, the robust resource allocation problem with activity splitting is investigated. More specifically, the uncertain environment is defined as stochastic activity durations, and the optimization objective is to generate a robust resource allocation schedule. For this problem, activities are allowed to be further split into certain subactivities under the constraints of the maximum number of splitting and the minimum execution time for each subactivity. With these two splitting constraints, it is assumed that activity splitting won’t increase the duration of the split activity. The resource requirements of the subactivities are the same as those of that activity, the sum of the durations of the subactivities are equal to that of the original activity, and there are precedence relations between the subactivities.Based on the problem description, the calculation method of free slacks and a new surrogate robustness measure are proposed with the consideration of activity splitting and resource flow network, and then the robust scheduling optimization model is constructed. The optimization objective is robustness maximization, and the constraints include precedence constraints, project due date constraint, the splitting constraints, resource flow constraints, and variable domain constraints. For the established model, there are four decision variables, which are respectively the number of subactivities for each activ
作者
马志强
徐小峰
何正文
王能民
MA Zhi-qiang;XU Xiao-feng;HE Zheng-wen;WANG Neng-min(School of Economics and Management,China University of Petroleum,Qingdao 266580,China;School of Management,Xi’an Jiaotong University,Xi’an 710049,China)
出处
《中国管理科学》
CSSCI
CSCD
北大核心
2022年第3期117-130,共14页
Chinese Journal of Management Science
基金
青岛市博士后应用研究项目(qdyy20200055)
中国石油大学(华东)自主创新科研计划项目(20CX06107A)
国家自然科学基金资助项目(71871222,71871176,71572138,71732006)。
关键词
鲁棒性调度
优化模型
遗传算法
活动可拆分
活动工期不确定
robust scheduling
optimization model
genetic algorithm
activity splitting
stochastic activity durations
