Sequential quadratic programming

Sequential quadratic programming, abbreviated SQP, is an iterative method for constrained nonlinear optimization. It is also known as the Lagrange-Newton method. The lead states that SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable, but not necessarily convex. In other words, it is a general-purpose way of minimizing a smooth function when the solution must also satisfy smooth constraints, and it does not demand the convexity that many other optimization methods assume.