Abstract
In order to enable energy-efficient operation of factory automation systems during non-productive (idling) phases, the energy-optimal sequence of operating modes has to be calculated. Due to modular structures and runtime constraints, the combinatorial optimization problems that have to be solved to calculate energy-minimizing schedules for today’s automation systems become extremely complex. In this paper, a novel domain-specific branch-and-bound algorithm is proposed that takes the structural knowledge about the automation system into account in order to attenuate the exponential complexity. Relying on a network of automation subsystems representing the switching and energetic operating behavior of the automation system, the method uses the minimal energy demand for unrelated subsystems, which can be efficiently calculated using off-the-shelf constraint optimization techniques, as lower bounds for the energy demand of the complete automation system. Evaluations indicate that the proposed procedure outperforms a complete enumeration in terms of computational time by more than 70 percent while assuring to identify the energy-optimal switching and operating sequences.
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Mechs, S., Lamparter, S., Peschke, J., Müller, J.P. (2013). Efficient Identification of Energy-Optimal Switching and Operating Sequences for Modular Factory Automation Systems. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_21
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DOI: https://doi.org/10.1007/978-3-642-38577-3_21
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