Common heat transfer fluids such as water, ethylene glycol, and engine oil have limited heat transfer capabilities due to their low heat transfer properties. Nanofluids are suspensions of nanoparticles in base fluids, a new challenge for thermal sciences provided by nanotechnology. In this study, we are to optimize and report the effects of various parameters such as the ratio of the thermal co...

In this study, teaching-learning-based optimization (TLBO) algorithm is employed for the first time for optimization of real world truss bridges. The objective function considered is the weight of the structure subjected to design constraints including internal stress within bar elements and serviceability (deflection). Two examples demonstrate the effectiveness of TLBO algorithm in optimizatio...

In the paper a linear-quadratic optimization problem (LCTOR) with unseparated two-point boundary conditions is considered. To solve this problem is proposed a new sweep algorithm which increases doubles the dimension of the original system. In contrast to the well-known methods, here it refuses to solve linear matrix and nonlinear Riccati equations, since the solution of such multi-point optimi...

Mixed-integer nonlinear optimization problems arise in scientific and operational applications ranging from the reordering of nuclear fuel rods to the design of wireless networks. We present some novel mixed-integer nonlinear optimization applications and review existing solution techniques. We also describe some experiments with nonlinear branch-and-bound branching techniques that lead us to p...

This contribution describes the development and implementation of a novel software toolbox, NDOT, for the dynamic optimization (open loop optimal control) of nonlinear processes. This modular and flexible toolbox combines the control vector parameterization approach with a number of local and global nonlinear programming solvers and suitable dynamic simulation methods. NDOT is able to solve dyn...

A numerical algorithm for approximate multi-parametric nonlinear programming is developed. It allows approximate solutions to nonlinear optimization problems to be computed as explicit piecewise linear functions of the problem parameters. In control applications such as nonlinear constrained model predictive control this allows efficient online implementation in terms of an explicit piecewise l...

From global to local convergence of interior methods for nonlinear optimization Paul Armand , Joël Benoist & Dominique Orban To cite this article: Paul Armand , Joël Benoist & Dominique Orban (2013) From global to local convergence of interior methods for nonlinear optimization, Optimization Methods and Software, 28:5, 1051-1080, DOI: 10.1080/10556788.2012.668905 To link to this article: http:/...

Sequential quadratic optimization algorithms are proposed for solving smooth nonlinear problems with equality constraints. The main focus is an algorithm the case when the...