This study presents a hybrid algorithm obtained by combining a genetic algorithm (GA) with successive quadratic sequential programming (SQP), namely GA-SQP. GA is the main optimizer, whereas SQP is ...

In this paper we present a filter sequential quadratic programming (SQP) algorithm for solving constrained optimization problems. This algorithm is based on the modified quadratic programming (QP) ...

A new penalty function for sequential quadratic programming algorithm is proposed for general nonlinear programming. The quadratic programming sub problem in which each iteration proceeds in two ...

MATLAB's fmincon() function in the Optimization Toolbox can find a local minimum solution for system optimization problems. It supports multiple algorithms such as: 'interior-point' (default) ...

In this paper we present a new sequential quadratic programming SQP algorithm that does not need any preprocessing phase. Its main features consist of not enforcing the Hessian to be positive definite ...

In this paper, a modified sequential quadratic programming (SQP)-based model predictive control (MPC) algorithm is developed and implemented for power plant cycling applications. These applications ...

GA-SQP and SQP algorithms have been executed 52 times. As shown in Table 9, GA-SQP algorithm allows to obtain 82.76% success solution and SQP algorithm allows to obtain only 18.29% success solution.

A filter SQP algorithm without a feasibility restoration phase *. Chungen Shen I,II; Wenjuan Xue III; Dingguo Pu I. I Department of Mathematics, Tongji University, China, 200092 . II Department of ...