Several methods have been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; a survey paper [7] provides an overview of var...
We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
In a distributed system, a number of application tasks may need to be assigned to different processors such that the system cost is minimized and the constraints with limited reso...
We model social choice problems in which self interested agents with private utility functions have to agree on values for a set of variables subject to side constraints. The goal...
We consider soft constraint problems where some of the preferences may be unspecified. This models, for example, settings where agents are distributed and have privacy issues, or ...
Mirco Gelain, Maria Silvia Pini, Francesca Rossi, ...