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

Just as in its 1st edition, this book starts with illustrations of the ubiquitous character of
optimization, and describes numerical algorithms in a tutorial way. It covers fundamental …

The sequential quadratic programming (SQP) algorithm has been one of the most
successful general methods for solving nonlinear constrained optimization problems. We …

We consider the optimal control of feedback linearizable dynamical systems subject to
mixed state and control constraints. In general, a linearizing feedback control does not …

Recent developments in numerical methods for solving large differentiable nonlinear
optimization problems are reviewed. State-of-the-art algorithms for solving unconstrained …

Nonlinearly constrained optimization problems can be solved by minimizing a sequence of
simpler unconstrained or linearly constrained subproblems. In this paper, we consider the …

This study presents a novel approach of hybrid modified Jaya and Technique for Order
Preference by Similarity to Ideal Solution (TOPSIS) optimization (MJTO) for efficiently …

Abstract In 1696, Johann Bernoulli solved the brachistochrone problem by an ingenious
method of combining Fermat's principle of minimum time, Snell's law of refraction and “finite …

The engineering feasibility of a space mission is overwhelmingly dictated by the amount of
propellant required to accomplish it. This requirement stems from the simple notion that if …

We compare and contrast a number of recent sequential quadratic programming (SQP)
methods that have been proposed for the solution of large-scale nonlinear programming …