Multi-objective Flexible Job-Shop Scheduling with an Ensemble Optimisation Model
Published in IEEE, 2022
Recommended citation: Y. H. Choo, Z. Cai, V. Le, M. Johnstone, W. K. Chan and D. Creighton, "Multi-objective Flexible Job-Shop Scheduling with an Ensemble Optimisation Model," 2022 IEEE Industrial Electronics and Applications Conference (IEACon), Kuala Lumpur, Malaysia, 2022, pp. 229-234, doi: 10.1109/IEACon55029.2022.9951770. https://doi.org/10.1109/IEACon55029.2022.9951770
Smart factories and intelligent manufacturing systems are the key drivers of knowledge economy in the era of Industry 4.0. One of the critical aspects is a flexible and optimised production planning and scheduling system. An efficient scheduling system can minimise the production cost and maximise machine utilization, leading to improvement in the production rate. In this study, we design an ensemble-based Harris’ Hawk optimisers (EN-HHO) to address the multi-objective flexible job shop problem (MOFJSP), which is an NP-hard and complex combinatorial task. The developed ensemble model is evaluated using well-known benchmark problems, and the results compare favourably with those from similar methods in the literature.