A New Genetic Algorithms combined with Learning Strategy for Flexible Job-shop Scheduling Problem

摘要

In this paper, we have proposed a new method based on genetic algorithms and the learning by partial injection of sequences for solving the Flexible Jobshop Scheduling Problem (FJSP). Computational experiments show that the AGAIS (II) algorithm outperforms the performance of the AGAIS (I). In fact, the AGAIS (II) gives better solutions than AGAIS (I) in a reasonable computation time.