Robust program scheduling optimization under uncertain environments
To improve the robustness and competitiveness of the program's scheduling,this study proposes an adjustable robust optimization method that combines robust scheduling of the projects with robust optimization of the program,considering the uncertainty of activity durations and project makespan.At the program level,a linear programming model for robust optimization is proposed to flexibly perform robust optimization based on the project results obtained from a multi-objective hyper-heuristic algorithm.Finally,numerical experiments are performed based on the data sets,and the sensitive analysis of the program parameters is performed.The results show that the two-layer robust optimization method can not only consider the uncertainties but also avoid operation efficiency losses due to overly conservative scheduling.
project schedulingprogramrobustranking of Pareto frontier solutionsrobust optimization
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