Optimization methods

Date	15/09/2006
Author	T. V. Tran, S. Brisset, P. Brochet
Affiliation	L2EP – EC Lille – France
Email	tran.tuan-vu@ec-lille.fr, stephane.brisset@ec-lille.fr, pascal.brochet@ec-lille.fr
Method	Sequential Quadratic Programming (SQP)
References	[1] Optimization Toolbox, Computation – Visualization – Programming, User’s Guide version 2. [2] P. Venkataraman, Applied Optimization with Matlab^Ò Programming, A Wiley - Interscience publication, John Wiley & Sons, New York, 2001.
Description of the method	The method Sequential Quadratic Programming is based on the calculation of gradient and derivation of the function objective with a generalization of Newton’s method for unconstrained optimization problems. At each major iteration, an approximation is made of the Hessian of the Lagrangian function using a quasi-Newton updating method. This is then used to generate a QP subproblem whose solution is used to form a search direction for a line search procedure.
Publication of the method

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