• Multimode time-cost-robustness trade-off project scheduling problem under uncertainty

      Li, Xue; He, Zhengwen; Wang, Nengmin; Vanhoucke, Mario (Journal of Combinatorial Optimization, 2020)
      The time/cost trade-off problem is a well-known project scheduling problem that has been extensively studied. In recent years, many researchers have begun to focus on project scheduling problems under uncertainty to cope with uncertain factors, such as resource idleness, high inventory, and missing deadlines. To reduce the disturbance from uncertain factors, the aim of robust scheduling is to generate schedules with time buffers or resource buffers, which are capped by project makespan and project cost. This paper addresses a time-cost-robustness trade-off project scheduling problem with multiple activity execution modes under uncertainty. A multiobjective optimization model with three objectives (makespan minimization, cost minimization, and robustness maximization) is constructed and three propositions are proposed. An epsilon-constraint method-based genetic algorithm along with three improvement measures is designed to solve this NP-hard problem and to develop Pareto schedule sets, and a large-scale computational experiment on a randomly generated dataset is performed to validate the effectiveness of the proposed algorithm and the improvement measures. The final sensitivity analysis of three key parameters shows their distinctive influences on the three objectives, according to which several suggestions are given to project managers on the effective measures to improve the three objectives.
    • On the performance of priority rules for the stochastic resource constrained multi-project scheduling problem

      Wang, Yanting; He, Zhengwen; Kerkhove, Louis-Phillipe; Vanhoucke, Mario (Computers & Industrial Engineering, 2017)
      The majority of research studies the resource constrained multi-project scheduling problem in a deterministic environment, regardless of the uncertainty nature of the environment. In this paper, we assume that the activity duration is a stochastic variable, and propose two new robustness measures to analyse the performance of priority rules under a stochastic environment. A full factorial experiment is designed to solve the problem and investigate the relationship between project characteristics and the performance of priority rules. Furthermore, a trade-off relationship between the quality and robustness is investigated and the best priority rules are recommended from both a project and portfolio managers perspective.