Abstract
Necessary and sufficient conditions for the problem of maximizing or minimizing a function subject to inequality constraints are given by a set of equalities and inequalities known as the Kuhn-Tucker conditions. These conditions can provide an analytic solution to the optimization problem if the artificial variables known as Lagrange multipliers can be eliminated. However, this is tedious to do by hand. This paper develops a computer program to assist in the solution process which combines symbolic computation and automated reasoning techniques. The program may also be useful for other problems involving algebraic reasoning with inequalities which employ general functions or symbolic parameters.
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Char, B.W., Macnaughton, A.R. & Strooper, P.A. Discovering inequality conditions in the analytic solution of optimization problems. J Autom Reasoning 5, 339–362 (1989). https://doi.org/10.1007/BF00248323
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DOI: https://doi.org/10.1007/BF00248323