Joshua Pulsipher
Joshua Pulsipher
Currently, all variables are freely discretized over internal collocation points. However, in certain instances (like control) it is desirable for control variables to stay constant over each finite element. We...
JuMP now supports specifying dual start values for constraints. Enabling this in InfiniteOpt will require that we create a data structure to store such information, since constraints don't have anything...
Currently, we define boundary conditions as constraints, but the model doesn't explicitly track/identify these. We should explicitly track these to enhance error checking and better support transformation methods. One possibility...
Using random field theory in combination with infinite-dimensional optimization denotes an interesting new class of optimization problems with diverse application. This generally corresponds to the case when an infinite parameter...
Currently, point variables inherit start values from infinite variables on creation. However, these are not updated when the start value function on the infinite variable is changed. This leads the...
Currently, we provide 2 different ways to define derivatives over restricted domains. ```julia model = InfiniteModel() @infinite_parameter(model, t in [0, 1]) @infinite_parameter(model, x in [-1, 1]) @variable(model, y, Infinite(t, x))...
Currently, higher-order derivatives are built recursively as 1st-order ones by introducing auxiliary variables. This impedes the use of higher-fidelity solution approaches. We should refactor the derivative modeling abstraction such that...
**Describe the feature you'd like** Allow this to plugin to effective dynamic simulators to simulate the model. This could be used to generate better guess values in accordance with #43....
**Describe the bug** Currently we support modeling of measures and derivatives that partially evaluate dependent parameter dependencies, however this cannot be transcripted in general. Fundamentally, this occurs because this produces...
Currently, when derivatives are evaluated for optimizer models, they are first transformed into a reduced InfiniteOpt expression and then transcripted into JuMP expressions. However, this workflow can be reworked to...