Zhao, Shuai, Dziurzanski, Piotr, Przewozniczek, Michal et al. (2 more authors) (Accepted: 2019) Cloud-based Dynamic Distributed Optimisation of Integrated Process Planning and Scheduling in Smart Factories. In: The Genetic and Evolutionary Computation Conference. , CZE (In Press)
Abstract
In smart factories, process planning and scheduling need to be performed every time a new manufacturing order is received or a factory state change has been detected. A new plan and schedule need to be determined quickly to increase the responsiveness of the factory and enlarge its profit. Simultaneous optimisation of manufacturing process planning and scheduling leads to better results than a traditional sequential approach but is computationally more expensive and thus difficult to be applied to real-world manufacturing scenarios. In this paper, a working approach for cloud-based distributed optimisation of process planning and scheduling is presented. It executes a multi-objective genetic algorithm on multiple subpopulations (islands). The number of islands is automatically decided based on the current optimisation state. A number of test cases based on two real-world manufacturing scenarios are used to show the applicability of the proposed solution.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Keywords: | Integrated process planning and scheduling,Multi-objective Genetic Algorithm,Function as a Service,Serverless Clouds |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 29 Apr 2019 09:10 |
Last Modified: | 06 Feb 2025 00:04 |
Status: | In Press |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145454 |
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