BibTeX
@ARTICLE{
         Schichl2012Adt,
       author = "Schichl, Hermann and Mark\'{o}t, Mih\'{a}ly Csaba",
       title = "Algorithmic differentiation techniques for global optimization in the {COCONUT}
         environment",
       journal = "Optimization Methods and Software",
       volume = "27",
       number = "2",
       pages = "359--372",
       year = "2012",
       doi = "10.1080/10556788.2010.547581",
       url = "http://www.tandfonline.com/doi/abs/10.1080/10556788.2010.547581",
       eprint = "http://www.tandfonline.com/doi/pdf/10.1080/10556788.2010.547581",
       abstract = "We describe algorithmic differentiation as it can be used in algorithms for global
         optimization. We focus on the algorithmic differentiation methods implemented in the COCONUT
         Environment for global nonlinear optimization. The COCONUT Environment represents each factorable
         optimization problem as a directed acyclic graph (DAG). Various inference modules implemented in
         this software environment can serve as building blocks for solution algorithms. Many of them use
         techniques based on various forms of algorithmic differentiation for computing approximations or
         enclosures of functions or their derivatives. The algorithmic differentiation in the COCONUT
         Environment not only provides point evaluations but also range enclosures of derivatives up to order
         3, as well as slopes up to order 2. Care is taken to ensure that rounding errors are treated
         correctly. The ranges of the enclosures can be tightened by combining the evaluation routines with
         constraint propagation. Advantages and pitfalls of this method are also outlined.",
       ad_area = "Optimization"
}