MOSAICmodeling enables a number of different advanced features based on the simulation of steady-state or dynamic system. Among these are the simultaneous and sequential optimization. A number of additional features, such as parameter estimation and chance-constrained optimization will be added subsequently.

Optimization inside MOSAICmodeling is currently limited to general Mixed-Integer NonLinear Programming (MINLP) problems:

\min_{u,y} f(x,u,y)

s.t. g(x,u,y) = 0,

x^L \leq x \leq x^U,

u^L \leq u \leq u^U,

y \in \mathcal{Z}^n,

y^L \leq y \leq y^U


Inequality constraints at the moment need to be manually reformulated as equality constraints by the introduction of slack variables s:

h(x,u,y) \geq 0 \Rightarrow h(x, u, y) - s = 0 with s \geq 0

Advanced Optimization Features

Follow the links below for detailed descriptions on how to use each feature.