Exact and Approximate Aggregation

  • Vladimir Tsurkov
Part of the Applied Optimization book series (APOP, volume 51)


When analyzing systems with a large number of parameters, the dimension of the original system may present insurmountable difficulties for the analysis. It may then be convenient to reformulate the original system in terms of substantially fewer aggregated variables, or macrovariables. In other words, an original system with an n-dimensional vector of states is reformulated as a system with a vector of dimension much less than n. The aggregated variables are either readily defined and processed, or the aggregated system may be considered as an approximate model for the original system. In the latter case, the operation of the original system can be exhaustively analyzed within the framework of the aggregated model, and one faces the problems of defining the rules for introducing macrovariables, specifying loss of information and accuracy, recovering original variables from aggregates, etc. These problems are addressed in this chapter.


Feasible Solution Original Problem Compatibility Condition Aggregation Operator Aggregate Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Vladimir Tsurkov
    • 1
  1. 1.Computing CenterRussian Academy of SciencesMoscowRussia

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