A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations

We study resource-constrained project scheduling problems with perturbation on activity durations. With the consideration of robustness and stability of a schedule, we model the problem as a multiobjective optimization problem. Three objectives-makespan minimization, robustness maximization, and stability maximization-are simultaneously considered. We propose a hybrid multiobjective evolutionary algorithm (H-MOEA) to solve this problem. In the process of the H-MOEA, the heuristic information is extracted periodically from the obtained nondominated solutions, and a local search procedure based on the accumulated information is incorporated. The results obtained from the computational study show that the proposed approach is feasible and effective for the resource-constrained project scheduling problems with stochastic durations.