Asymptotically Exact Minimizations for Optimal Management of Public Finances
The algorithms for asymptotically exact minimizations in Karush-Kuhn-Tucker methods recently published have been considered to be effective on linear or non-linear optimizations problems, differentiable and under inequality constraints. The algorithms conceptions as well as the test results on reference and academic problems are published in [1, 2]. The purpose of this paper is to use these algorithms to solve a specific large-scale problem: the optimal management of public finances. We give a formal study on the design of the models interpreting this problem and solve it thanks to our algorithms to determine at each moment, the optimal recipe and the optimal expenditure that the Government of a State must realize in order to achieve its goals. The numerical results obtained testify the efficiency of our algorithms on large-scale problems.
KeywordsAugmented Lagrangian methods Numerical experiments Approximate KKT point Public finances Adjustment costs
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