A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem

In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each project activity. To solve the problem, we propose a hybrid evolutionary algorithm. This algorithm incorporates a diversity-adaptive simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the fluctuation of diversity of evolutionary algorithm population. The performance of the hybrid evolutionary algorithm on six different instance sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid evolutionary algorithm significantly outperforms the previous algorithms.