In my previous blog posts I demonstrated how to use nonlinear programming in R for solving an optimization problem. To be more specific, I used the Augmented Lagrange Multiplier (ALM) method for solving a specific engineering optimization problem.
In this blog post I will again employ the ALM method for solving an engineering optimization problem. This time I will analyze a two-bar bracket design subjected to a load. The goal of this optimization problem is to find the minimal mass of the design so that the bracket will support the load without structural failure.
Continue reading Using nonlinear programming for solving mechanical engineering problems: Designing a two-bar bracket
Nonlinear programming is used for solving optimization problems. The goal of such optimization problems is to minimize (or maximize) some objective function. However, these optimization problems often specify a number of constraints. Nonlinear programming is applied when the objective function or some of the specified constraints are nonlinear.
The following R code demonstrates how to solve an optimization problem using nonlinear programming. More specifically, the R code uses the Augmented Lagrange Multiplier (ALM) method for finding the minimum design weight of a circular thin walled column subjected to a buckling load.
Continue reading Using nonlinear programming for solving mechanical engineering problems: Designing a column subjected to a buckling load