Nonlinear Approaches for the Solution of Hard Optimization Problems with Integer Variables
|Giorgio Grani||Dottorando/Assegnista/Specializzando componente il gruppo di ricerca|
Many real-world problems in the areas of Applied Sciences, Engineering and Economics, are modeled involving integer and 0-1 variables, in order to reflect discrete quantities, logical relationships or decisions.
When nonlinear functions are necessary to model the
nonlinear context of the problem, we are in the field of
Mixed-Integer Nonlinear Programming (MINLP).
MINLP problems combine all the difficulties of both Mixed Integer Programs (MIP) and NonLinear Programs (NLP), which are among the class of theoretically difficult problems (NP-complete).
Therefore, the design of efficient solution methods for MINLP problems is a big challenge for people working in Operations Research.
The research activity will be devoted to
- the study and the definition of new optimization methodologies to deal with specific combinatorial and MINLP problems,
- the definition and the use of new algorithms for handling real-world revenue management problems.