Optimization in large partly nonlinear systems

  • Arne Drud
Mathematical Programming
Part of the Lecture Notes in Computer Science book series (LNCS, volume 41)


This paper describes a method for optimizing large partly nonlinear systems. The method is based on the GRG-algorithm, that solves problems with nonlinear objective function and nonlinear equality constraints. The original GRG-algorithm is described and its relations with LP are stressed. Some storage problems in large problems are discussed, and a special inversion procedure for the GRG-algorithm is presented. Some special kinds of constraints, inequalities and linear constraints, are considered, and it is shown, how their special features can be utilized. Finally some computational results with the method are given.


Basic Variable Inversion Procedure Pivot Element Nonbasic Variable Nonlinear Objective Function 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1976

Authors and Affiliations

  • Arne Drud
    • 1
  1. 1.IMSOR The Institute of Mathematical Statistics and Operations ResearchThe Technical University of DenmarkLyngbyDenmark

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