Advances in Production Engineering & Management
Volume 14 | Number 3 | September 2019 | pp 271–283
https://doi.org/10.14743/apem2019.3.327
Dynamic scheduling in the engineer-to-order (ETO) assembly process by the combined immune algorithm and simulated annealing method
Jiang, C.; Xi, J.T.
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A B S T R A C T
With the increasing demand for customization, the engineer-to-order (ETO) production strategy plays an increasingly important role in today's manufacturing industry. The dynamic scheduling problem in ETO assembly process was investigated. We developed the mathematical model to represent the problem. In order to reduce rescheduling frequency, we introduced the concept of starting time deviation and improved the rolling horizon driven strategy. We proposed the hybrid algorithm combining immune algorithm (IA) and simulated annealing (SA) with the minimization of the rescheduling cost as the objective. The IA was designed as the global search process and the SA was introduced to improve the local searching ability. The scenario-based approach was used to model the disruptions affecting the tasks to be executed. Performance of the rolling horizon driven strategy and the hybrid algorithm were evaluated through simulations, the experiment analysis showed the best parameters of rolling horizon methods and demonstrated the feasibility of the hybrid algorithm. The hybrid algorithm was tested on different scale benchmark instances and the case that collected from a steam turbine assembly shop. The quality of solution in terms of cost obtained by the hybrid algorithm was found superior to the other three algorithms proposed in the literature.
A R T I C L E I N F O
Keywords • Engineer-to-order (ETO); Assembly process; Dynamic scheduling; Rescheduling; Rolling horizon; Immune algorithm; Simulated annealing
Corresponding author • Jiang, C.
Article history • Received 16 April 2019, Revised 14 September 2019, Accepted 16 September 2019
Published on-line • 30 September 2019
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