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A Constructive Cooperative Coevolutionary Algorithm Applied to Press Line Optimisation
University West, Department of Engineering Science, Division of Automation Systems. (PTW)ORCID iD: 0000-0002-0044-2795
University West, Department of Engineering Science, Division of Automation and Computer Engineering. (PTW)ORCID iD: 0000-0002-8878-2718
University West, Department of Engineering Science, Division of Automation and Computer Engineering. (PTW)ORCID iD: 0000-0002-6604-6904
University West, Department of Technology, Mathematics and Computer Science, Division for Electrical Engineering and Land Surveying. Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden.
2014 (English)In: Proceedings of the 24th International Conference on Flexible Automation and Intelligent Manufacturing: Capturing Competitive Advantage via Advanced Manufacturing and Enterprise Transformation / [ed] F. Frank Chen, Lancaster, PA, USA: DEStech Publications, Inc. , 2014, p. 909-916Conference paper, Published paper (Refereed)
Abstract [en]

Simulation-based optimisation often considers computationally expensive problems. Successfully optimising such large scale and complex problems within a practical time frame is a challenging task. Optimisation techniques to fulfil this need to be developed. A technique to address this involves decomposing the considered problem into smaller subproblems. These subproblems are then optimised separately. In this paper, an efficient algorithm for simulation-based optimisation is proposed. The proposed algorithm extends the cooperative coevolutionary algorithm, which optimises subproblems separately. To optimise the subproblems, the proposed algorithm enables using a deterministic algorithm, next to stochastic genetic algorithms, getting the flexibility of using either type. It also includes a constructive heuristic that creates good initial feasible solutions to reduce the number of fitness calculations. The extension enables solving complex, computationally expensive problems efficiently. The proposed algorithm has been applied on automated sheet metal press lines from the automotive industry. This is a highly complex optimisation problem due to its non-linearity and high dimensionality. The optimisation problem is to find control parameters that maximises the line’s production rate. These control parameters determine velocities, time constants, and cam values for critical interactions between components. A simulation model is used for the fitness calculation during the optimisation. The results show that the proposed algorithm manages to solve the press line optimisation problem efficiently. This is a step forward in press line optimisation since this is to the authors’ knowledge the first time a press line has been optimised efficiently in this way.

Place, publisher, year, edition, pages
Lancaster, PA, USA: DEStech Publications, Inc. , 2014. p. 909-916
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Mechatronics
Identifiers
URN: urn:nbn:se:hv:diva-6710ISBN: 978-1-60595-173-7 (print)OAI: oai:DiVA.org:hv-6710DiVA, id: diva2:754165
Conference
24th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM)
Available from: 2014-10-09 Created: 2014-09-25 Last updated: 2016-02-08Bibliographically approved
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Glorieux, EmileSvensson, BoDanielsson, Fredrik

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