An Adaptive Hybrid Evolutionary Approach for a Project Scheduling Problem that Maximizes the Effectiveness of Human Resources

Abstract

In this paper, an adaptive hybrid evolutionary algorithm is proposed to solve a project scheduling problem. This problem considers a valuable optimization objective for project managers. This objective is maximizing the effectiveness of the sets of human resources assigned to the project activities. The adaptive hybrid evolutionary algorithm utilizes adaptive processes to develop the different stages of the evolutionary cycle (i.e., adaptive parent selection, survival selection, crossover, mutation and simulated annealing processes). These processes adapt their behavior according to the diversity of the algorithm’s population. The utilization of these processes is meant to enhance the evolutionary search. The performance of the adaptive hybrid evolutionary algorithm is evaluated on six instance sets with different complexity levels, and then is compared with those of the algorithms previously reported in the literature for the addressed problem. The obtained results indicate that the adaptive hybrid evolutionary algorithm significantly outperforms the algorithms previously reported.