0393327 20240103202652.420130627235959.9 10.1007/978-3-319-00551-5_33 8 s. P cav_un_epca*0393326978-3-319-00550-8XVIIIAdvances in Intelligent Systems and Computing267-274ChamSpringer2013 Empirical function minimization black-box modeling simplification refining dynamic building control cav_un_auth*0292010 Macek Karel Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B 90 Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0292027 Rojíček J. CZ cav_un_auth*0052682 Bičík V. CZ http://library.utia.cas.cz/separaty/2013/AS/macek-trajectory optimization under changing.pdf 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 dimen- sions that make the problems complex or even computationally infeasble. 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. cav_un_auth*0292011 10th International Symposium on Distributed Computing and Artificial Intelligence Salamanca 22.05.2013-24.05.2013 ES 2014 BB 3 PR RVO:67985556 http://hdl.handle.net/11104/0222068 2013 cav_un_epca*0393326 Distributed Computing and Artificial Intelligence Advances in Intelligent Systems and Computing XVIII 978-3-319-00550-8 267 274 Distributed Computing and Artificial Intelligence Cham Springer 2013 217 XVIII