In that case, critical points coincide with KKT points. When the data are semi-algebraic or real analytic our method applies (for instance) to the study of various sequential quadratic programming ...

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse after every step of the method.

This paper shows a method for solving linear programming problems that includes Interval Type-2 fuzzy constraints. The proposed method finds an optimal solution in these conditions using convex ...

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NVIDIA's cuOpt leverages GPU technology to drastically accelerate linear programming, achieving performance up to 5,000 times faster than traditional CPU-based solutions.

A method is described for converting a boolean expression to a disjunctive normal equivalent (two level OR-AND circuit) which is minimal under some criterion presented in advance, as for example, the ...

Linear programming provides methods for computing the most practical solutions in production, operations, and supply planning and in the control of complex processes. The introduction of linear ...

Therefore, in order to combine the advantages of a linear encoder and nonlinear decoder, we developed the neural principal component analysis (nPCA) method, which is a linear dimensionality reduction ...