考虑模糊工序工期的重复性项目时间费用权衡优化

doi:10.3969/j.issn.1007-7375.230104

摘要/Abstract

摘要： 为了减少不确定性对项目业绩目标的影响，提高进度计划的鲁棒性，研究模糊工序工期下的重复性项目离散时间费用权衡问题。通过模糊风险度量，建立考虑决策者风险偏好的模糊机会约束规划模型，目标是确定所有工序的最优执行模式 (即模式列表)，从而在满足事先设定的工期延误和费用超支风险水平条件下最小化项目预算。提出模式列表已知条件下，计算模糊总工期和模糊总费用隶属度函数的正向递归过程，并据此设计搜索最优模式列表的基于电磁机制的改进遗传算法 (GA-EM)。利用一个实际工程案例验证算法的有效性，并通过数值实验分析算法的计算性能。结果表明，GA-EM能够给出满足给定工期延误和费用超支风险水平的模糊进度计划，预算的平均和最大百分比误差分别不大于0.096%和0.239%。

关键词: 时间费用权衡, 重复性项目, 模糊机会约束规划, 遗传算法

Abstract: In order to reduce the impact of uncertainty on project performance objectives and improve the robustness of scheduling, the discrete time-cost tradeoff problem for repetitive projects with fuzzy activity durations is investigated. A fuzzy chance-constrained programming model considering the risk preferences of decision makers is developed by means of fuzzy risk measurement to determine the optimal execution modes for all activities (i.e., mode list), thereby to minimize the project budget while meeting the pre-speci?ed risk levels of project delays and cost overruns. Given a known mode list, a forward recursive process for calculating the membership functions of fuzzy project duration and fuzzy total cost is proposed, while an improved genetic algorithm based on electromagnetic mechanism (GA-EM) for searching the optimal mode list is designed accordingly. The effectiveness of the algorithm is veri?ed using a real-life engineering case, and the computational performance of the algorithm is analyzed via numerical experiments. Results show that GA-EM can provide a fuzzy schedule that satisfies the given levels of schedule delays and cost overrun risks, with the average and maximum percentage deviations in the budget not exceeding 0.096% and 0.239%, respectively.

Key words: time-cost tradeoff, repetitive projects, fuzzy chance-constrained programming, genetic algorithm

中图分类号:

F402
N949

邹鑫, 陈丹昊, 张立辉. 考虑模糊工序工期的重复性项目时间费用权衡优化[J]. 工业工程, 2024, 27(4): 150-160,170.

ZOU Xin, CHEN Danhao, ZHANG Lihui. Time-Cost Tradeoff Optimization for Scheduling Repetitive Projects with Fuzzy Activity Durations[J]. Industrial Engineering Journal, 2024, 27(4): 150-160,170.

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