In this paper, we propose a converting technique based method to solve nonlinear multi-commodity network flow (NMNF) problems with a large number of capacity constraints and discuss the associated implementation. We have combined this method with a successive quadratic programming (SQP) method and a parallel dual-type (PDt) method possessing decomposition effects. We have tested our method in s...

A simple scheme is proposed for handling nonlinear equality constraints in the context of a previously introduced sequential quadratic programming (SQP) algorithm for inequality constrained problems, generating iterates satisfying the constraints. The key is an idea due to Mayne and Polak (Math. Progr., vol. 11, pp. 67{80, 1976) by which nonlinear equality constraints are treated as \"-type con...

We consider a combined IPM-SQP method to solve smooth nonlinear optimization problems, which may possess a large number of variables and a sparse Jacobian matrix of the constraints. Basically, the algorithm is a sequential quadratic programming (SQP) method, where the quadratic programming subproblem is solved by a primal-dual interior point method (IPM). A special feature of the algorithm is t...

By enabling constraint-aware online model adaptation, predictive control using Gaussian process (GP) regression has exhibited impressive performance in real-world applications and received considerable attention the learning-based community. Yet, solving resulting optimal problem real-time generally remains a major challenge, due to i) increased number of augmented states optimization problem, ...

Process optimization problems are frequently characterized by large models, with many variables and constraints but relatively few degrees of freedom. Thus, reduced Hessian decomposition methods applied to Successive Quadratic Programming (SQP) exploit the low dimensionality of the subspace of the decision variables, and have been very successful for a wide variety of process application. Howev...

Polymer:fullerene bulk heterojunction (BHJ) solar cell active layers can be created by traditional blend casting (BC), where the components are mixed together in solution before deposition, or by sequential processing (SqP), where the pure polymer and fullerene materials are cast sequentially from different solutions. Presently, however, the relative merits of SqP as compared to BC are not full...

In this paper, we propose an inexact alternating direction method with square quadratic proximal  (SQP) regularization for  the structured variational inequalities. The predictor is obtained via solving SQP system  approximately  under significantly  relaxed accuracy criterion  and the new iterate is computed directly by an explicit formula derived from the original SQP method. Under appropriat...

This paper proposes a hybrid technique combining a new heuristic algorithm named seeker optimization algorithm (SOA) and sequential quadratic programming (SQP) method for solving dynamic economic dispatch problem with valve-point effects. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient (EG) by evaluating the...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can ...