Solving Nonlinear Economic Planning Models Using GRG Algorithms

  • Leon Lasdon
  • Alexander Meeraus

Abstract

With the concept of optimization being such a central theme in economic theory, planning economists have always been attracted to mathematical programming as it provides a natural framework of analysis for theoretical and applied work. Although, nonlinear optimizing economic planning models have been specified and studied for more than 20 years [4, 17] few were ever solved on a routine basis. This stands in sharp contrast to linear programming models which, due to highly reliable (commercial) software are the workhorses of many planning agencies. Even today, most large-scale nonlinear planning models are solved with specifically designed algorithms, tailored around some high performance LP system [9, 14, 16].

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Copyright information

© Springer-Verlag Berlin Heidelberg 1979

Authors and Affiliations

  • Leon Lasdon
    • 1
  • Alexander Meeraus
    • 2
  1. 1.University of TexasAustinUSA
  2. 2.Development Research CenterWorld BankUSA

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