A sampling approach for proactive project scheduling under generalized time-dependent workability uncertainty

• Main Authors: SONG, Wen, KANG, Donghun, ZHANG, Jie, CAO, Zhiguang, XI, Hui
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Branch-and-bound algorithms; Empirical evaluations; Partial order schedules; Proactive scheduling; Real-world scenario; Sample average approximation; Stochastic optimization model; Uncertainty distributions; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/8196; https://ink.library.smu.edu.sg/context/sis_research/article/9199/viewcontent/A_Sampling_Approach_for_Proactive_Project_Scheduling_under_Generalized_Time_dependent_Workability_Uncertainty.pdf
• Institution: Singapore Management University

In real-world project scheduling applications, activity durations are often uncertain. Proactive scheduling can effectively cope with the duration uncertainties, by generating robust baseline solutions according to a priori stochastic knowledge. However, most of the existing proactive approaches ass...