Trajectory Optimization under Changing Conditions through Evolutionary Approach and Black-Box Models with Refining

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 217)


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.


Empirical function minimization black-box modeling simplification refining dynamic building control 


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Karel Macek
    • 1
    • 2
  • Jiří Rojíček
    • 1
  • Vladimír Bičík
    • 1
  1. 1.Honeywell LaboratoriesPragueCzech Republic
  2. 2.Institute of Information Theory and AutomatizationAcademy of Scienced of the Czech RepublicPragueCzech Republic

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