Multi-Objective Design using Sequential Quadratic programming & Weighted Sum approach. The purpose of this exercise is to design a cantilever cylindrical support column of minimum mass for a new water ...

A SQP algorithm implementation for solving nonlinear constrained optimization problems - Releases · spiroskou/Sequential-Quadratic-Programming-method-Implementation-in-Matlab ...

This paper reviews the integrated perturbation analysis - sequential quadratic programming (IPA-SQP) approach. The IPA-SQP approach has been proposed to address computational challenges in nonlinear ...

Jérôme Bolte, Edouard Pauwels, Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs, Mathematics of Operations Research, Vol. 41, No. 2 (May 2016), ...

This article proposes a centralized and distributed model based on nonlinear programming (NLP) for optimal power flow (OPF) analysis in power distribution networks, solved with the Sequential ...

ABSTRACT: 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 ...

This paper presents a feedrate optimization for spline toolpaths, performed via two steps: Linear Programming (LP) to obtain a fast and approximate solution followed by Sequential Quadratic ...

Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we ...