0423196 20240903204256.120140226235959.9 12 s. cav_un_epca*04231952255-286315 (2013)53-64 Evolutionary algorithms Black box modeling Simplification Refining HVAC Load shedding Communication infrastructure cav_un_auth*0292010 Macek Karel Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0292027 Rojíček J. CZ cav_un_auth*0301156 Kontes G. GR cav_un_auth*0301157 Rovas D. V. GR http://library.utia.cas.cz/separaty/2014/AS/macek-0423196.pdf GA13-13502S GA ČR cav_un_auth*0292725 The solution of repeated fixed-horizon trajectory optimization problems of processes that are either too difficult or too complex to be described by physicsbased models can pose formidable challenges. Very often, soft-computing methods - e.g. black-box modeling and evolutionary optimization - are used. These approaches are ineffective or even computationally intractable for searching high-dimensional parameter spaces. In this paper, a structured iterative process is described for addressing such problems: the starting point is a simple parameterization of the trajectory starting with a reduced number of parameters; after selection of values for these parameters so that this simpler problem is covered satisfactorily, a refinement procedure increases the number of parameters and the optimization is repeated. This continuous parameter refinement and optimization process can yield effective solutions after only a few iterations. 2014 BC 4 RVO:67985556 http://hdl.handle.net/11104/0231499 cav_un_auth*0299369 Honeywell Prague Laboratory CZ S 2013 cav_un_epca*0423195 Advances in Distributed Computing and Artificial Intelligence Journal 2255-2863 2255-2863 Roč. 1 č. 5 2013 53 64