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Γ-robust optimization of project scheduling problems
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DOI：10.1016/j.cor.2023.106453.png)
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Abstract
En 中文
In this paper, we investigate the problem of finding a robust baseline schedule for the project scheduling problem under uncertain process times. We assume that the probability distribution for the duration is unknown, but an estimate is given along with an interval in which this time can vary. At most Gamma of the tasks will deviate from the estimated time. We present two approaches to solving this problem. The first approach treats the problem of determining the earliest guaranteed finish times and can be solved in polynomial time by an extension of the critical path method. The second is a two-stage approach that determines the baseline schedule in the first stage and an adaptation to the scenario in the second stage. We show strong NP-hardness of the second stage problem and introduce a novel formulation. From this formulation we derive an exact algorithm and three heuristics. A computational study on benchmark instances shows that the heuristics perform well on larger instances.
Keywords:
Robust project scheduling
Budgeted uncertainty
Two-stage robust optimization
Heuristics
Mixed-integer programming
Journal
C
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