Scheduling Projects by a Hybrid Evolutionary Algorithm with Self-Adaptive Processes

VIRGINIA YANNIBELLI; ANALÍA AMANDI

LECTURE NOTES IN COMPUTER SCIENCE

Springer

Lugar: Heidelberg; Año: 2015 vol. 9413 p. 401 - 412

0302-9743

In this paper, we present a hybrid evolutionary algorithm with self-adaptive processes to solve a known project scheduling problem. This problem takes into consideration an optimization objective priority for project managers: to maximize the effectiveness of the sets of human resources assigned to the project activities. The hybrid evolutionary algorithm integrates self-adaptive processes with the aim of enhancing the evolutionary search. The behavior of these processes is self-adaptive according to the state of the evolutionary search. The performance of the hybrid evolutionary algorithm is evaluated on six different instance sets and then is compared with that of the best algorithm previously proposed in the literature for the addressed problem. The obtained results show that the hybrid evolutionary algorithm considerably outperforms the previous algorithm.-