Publication details
Conference Paper (international conference)
Trajectory Optimization under Changing Conditions through Evolutionary Approach and Black-Box Models with Refining
, ,
: Distributed Computing and Artificial Intelligence, p. 267-274
: 10th International Symposium on Distributed Computing and Artificial Intelligence, (Salamanca, ES, 22.05.2013-24.05.2013)
: Empirical function minimization, black-box modeling, simplification, refining, dynamic building control
: 10.1007/978-3-319-00551-5_33
: http://library.utia.cas.cz/separaty/2013/AS/macek-trajectory optimization under changing.pdf
(eng): 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.
: BB