Abstract
In this paper, we present Optimisation as a Service (OaaS) for an integrated process planning and scheduling in smart factories based on a distributed multi-criteria genetic algorithm (GA). In contrast to the traditional distributed GA following the island model, the proposed islands are executed asynchronously and exchange solutions at time points depending solely on the optimisation progress at each island. Several solutions’ exchange strategies are proposed, implemented in Amazon Elastic Container Service for Kubernetes (Amazon EKS) and evaluated using a real-world manufacturing problem.
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Notes
- 1.
We do not enforce the choice of quality indicator applied in the algorithm, but assume that a higher quality value indicates a higher quality of the optimisation result.
- 2.
1 ECU is defined as the compute power of a 1.0–1.2 GHz server CPU from 2007.
- 3.
The current costs can be found at https://aws.amazon.com/eks/pricing/.
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The authors acknowledge the support of the EU H2020 SAFIRE project (Ref. 723634).
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Zhao, S., Mei, H., Dziurzanski, P., Przewozniczek, M., Indrusiak, L.S. (2019). Cloud-Based Integrated Process Planning and Scheduling Optimisation via Asynchronous Islands. In: Djemame, K., Altmann, J., Bañares, J., Agmon Ben-Yehuda, O., Naldi, M. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2019. Lecture Notes in Computer Science(), vol 11819. Springer, Cham. https://doi.org/10.1007/978-3-030-36027-6_21
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