MiCoS can be applied to both early and late stage formulation processing.
A hybrid approach to construct prediction intervals of marginal clearing prices (MCPs) with a two-stage formulation is proposed in [17].
To adequately deal with this uncertainty, we employ a two-stage formulation where the operational parameters can be adapted to the realization of the uncertainty while the design parameters are the first-stage decisions.
The two-stage formulation can handle problems in which all design decisions are made up front and operating parameters act as 'recourse' decisions that can be varied from one time period to next based on realized values of uncertain parameters.
The two-stage formulation can handle problems in which all design decisions are made up front and operating parameters act as 'recourse' decisions that can be varied from one time period to another based on realized values of uncertain parameters.
Chen and Lee (2004) proposed a multi-period multi-product multi-stage formulation with multi-incompatible objectives of a multiple stage SCN as an MINLP, where fuzzy sets were investigated to explain the uncertainties contained in product prices and market demands.
The volume of material available for particle analysis is often very limited, especially in early stage formulation development.
In Section 3.1 we present such a standard multi-stage formulation and give references to Bock's direct multiple shooting method.
In the formulation development area, in silico predictive tools and model-based IVIVC approaches supported formulation development and life-cycle management resulting in more successful late stage formulation trials and also regulatory success.
Modeled as an optimal control problem, we demonstrate how incorporation of product specification bands leads to multi-stage formulations that greatly improve process performance and significantly reduce off-grade product.
