This article provides an algorithm that is dedicated to repeated trajectory optimization with a fixed horizon and addresses processes that are difficult to describe by the established laws of physics. Typically, soft-computing methods are used in such cases, i.e. black-box modeling and evolutionary optimization. Both suffer from high dimensions that make the problems complex or even computationally infeasible. We propose a way how to start from very simple problems and - after the simple problems are covered sufficiently - proceed to more complex ones. We provide also a case study related to the dynamic optimization of the HVAC (heating, ventilation, and air conditioning) systems. © Springer International Publishing Switzerland 2013.
CITATION STYLE
Macek, K., Rojíček, J., & Bičík, V. (2013). Trajectory optimization under changing conditions through evolutionary approach and black-box models with refining. Advances in Intelligent Systems and Computing, 217, 267–274. https://doi.org/10.1007/978-3-319-00551-5_33
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