Nonlinear Approaches for the Solution of Hard Optimization Problems with Integer Variables

Proponente Marianna De Santis - Professore Associato
Sottosettore ERC del proponente del progetto
Componenti gruppo di ricerca
Componente Categoria
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.


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