In this paper, we propose a modified trust-region filter method algorithm for Minimax problems, which based on the framework of SQP-filter method and associated with the technique of nonmonotone method. We use the SQP subproblem to acquire an attempt step, and use the filter to weigh the effect of the attempt step so as to avoid using penalty function. The algorithm uses the Lagrange function a...

Sequential quadratic programming (SQP) methods for nonlinearly constrained optimization typically use a merit function to enforce convergence from an arbitrary starting point. We define a smooth augmented Lagrangian merit function in which the Lagrange multiplier estimate is treated as a separate variable, and inequality constraints are handled by means of non-negative slack variables that are ...

NE/SQP is a recent algorithm tha t has proven quite effective for solving the pure and mixed forms of the nonlinear complementarity problem (NCP). NE/SQP is robust in the sense that i ts direction-finding subproblems are always solvable; in addition, the convergence rate of this method is Q-quadratic. In this paper we consider a generalized version of NE/SQP proposed by Pang and Qi, that is sui...

NE/SQP is a recent algorithm that has proven quite eeective for solving the pure and mixed forms of the nonlinear complementarity problem (NCP). NE/SQP is robust in the sense that its direction-nding subproblems are always solvable; in addition, the convergence rate of this method is Q-quadratic. In this paper we consider a generalized version of NE/SQP proposed by Pang and Qi, that is suitable...

For the sequential quadratic programming method (SQP), we show that close to a solution satisfying the same assumptions that are required for its local quadratic convergence (namely, uniqueness of the Lagrange multipliers and the second-order sufficient optimality condition), the direction given by the SQP subproblem using the Hessian of the Lagrangian is a descent direction for the standard l1...

In this paper, an integration of Improve Particle Swarm Optimization (IPSO) in combination with Successive Quadratic programming (SQP) so called IPSO-SQP algorithm is proposed to solve time optimal bang-bang control problems. The procedure is found not sensitive to the initial guess of the solution. Due to random selection in the first stage of the search process, the chance of converging to th...

Our goal is to identify the volatility function in Dupire’s equation from given option prices. Following an optimal control approach in a Lagrangian framework, we propose a globalized sequential quadratic programming (SQP) algorithm with a modified Hessian – to ensure that every SQP step is a descent direction – and implement a line search strategy. In each level of the SQP method a linear–quad...