Application of an evolutionary algorithm-based ensemble model to job-shop scheduling
Document Type
Article
Publication Date
1-1-2019
Abstract
In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems. © 2017, Springer Science+Business Media New York.
Keywords
Ensemble model, Evolutionary algorithm, Job-shop scheduling, Multi-objective optimisation
Divisions
fsktm
Funders
Collaborative Research in Engineering, Science and Technology (CREST) (Grant No. P05C2-14)
Publication Title
Journal of Intelligent Manufacturing
Volume
30
Issue
2
Publisher
Springer Verlag