This paper introduces a new approach to sequential quadratic programming. Upon application of the orthogonal-decomposition algorithm and the Gerschgorin Theorem for the stabilization of the Hessian matrix in the quadratic-programming solution, this novel approach offers an alternative to existing methods that, additionally, dispenses with a feasible initial guess.

Issue Section:
Technical Papers
Keywords:
design engineering, quadratic programming, optimisation, Hessian matrices, iterative methods, matrix algebra, eigenvalues and eigenfunctions
Topics:
Algorithms, Optimization, Quadratic programming, Chain, Eigenvalues, Theorems (Mathematics), Design, Linear systems
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