When applying the sequential quadratic programming (SQP) algorithm to topology optimization, using quasi-Newton methods or calculating Hessian matrix directly will result in a considerable amount of calculation, making it computationally infeasible when number optimization variables is large. To solve above problems, this paper creatively proposes method for approximate structural with minimum ...

Aiming at the problem that modeling and solving method of combined heat power (CHP) unit variable load control process is challenging to meet demand for efficient analysis complex systems, this paper proposes a based on sequential quadratic programming interior point (SQP-IPM) alternating solution dynamic optimization CHP process. Firstly, by constructing mechanism model, multi-variable coordin...

Aiming at complex road conditions and difficult path planning of semi-structured roads in a park, robust method based on sequential quadratic programming (SQP) algorithm optimization is proposed. Firstly, an improved vector field histogram (VFH) used to determine the optimal passable area, then determination target state given area; Secondly, according starting point state, description obstacle...

In (Boggs, Tolle and Kearsley 1994b) the authors introduced an eeective algorithm for general large scale nonlinear programming problems. In this paper we describe the theoretical foundation for this method. The algorithm is based on a trust region, sequential quadratic programming (SQP) technique and uses a special auxiliary function, called a merit function or line-search function, for assess...

We provide an eeective and eecient implementation of a sequential quadratic programming (SQP) algorithm for the general large scale nonlinear programming problem. In this algorithm the quadratic programming subproblems are solved by an interior point method that can be prematurely halted by a trust region constraint. Numerous computational enhancements to improve the numerical performance are p...

Abstract In this paper, the mathematical models for flow and heat-transfer analysis of a non-Newtonian fluid with axisymmetric channels porous walls are analyzed. The governing equations problem derived by using basic concepts continuity momentum equations. Furthermore, artificial intelligence-based feedforward neural networks (ANNs) utilized hybridization generalized normal-distribution optimi...

A two-stage stochastic programming model is established to minimize EV's expected total journey time under traffic conditions, by jointly optimizing the allocation of chargers and distribution EV flows. Based on sample average approximation, a feasible deterministic equivalent original problem obtained. Then, hybrid solution method, composing Tabu-based search sequential quadratic (SQP), propos...

We develop and analyze a trust-region sequential quadratic programming (SQP) method for the solution of smooth equality constrained optimization problems, which allows the inexact and hence iterative solution of linear systems. Iterative solution of linear systems is important in large-scale applications, such as optimization problems with partial differential equation constraints, where direct...

In this paper, we propose a trust region filter method for minimax problems. Based on the filter technique, the minimax problem is transformed to a constrained optimization problem and solved by the traditional filter idea. In the presented algorithm, the acceptable criterion of the trial points is relaxed, so compared to the existed SQP and Newton-type methods for minimax method, this method i...