Optimization methods

Date	31/08/2007
Author	Mathworks
Affiliation	Mathworks
Email
Method	Sequential Quadratic Programming (SQP)
References	[1] Optimization Toolbox, Computation – Visualization – Programming, User’s Guide version 2. [2] P. Venkataraman, Applied Optimization with Matlab^® Programming, A Wiley - Interscience publication, John Wiley & Sons, New York, 2001.
Description of the method	SQP method represents the state of the art in nonlinear programming methods. It is an iterative method, which solves a quadratic problem (QP) at each iteration. It 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.

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