ALGORITHMS FOR OPTIMIZATION PROBLEMS WITH FRACTIONAL RESOURCES

We consider a class of optimization problems having a distinctive feature: both discrete and continuous decisions need to be taken simultaneously. These problems arise in many practical applications, for example broadband telecommunications and green transportation problems, where resources are available, that can be fractionally consumed or assigned. These problems are proven of being harder than their purely discrete counterpart. We propose effective methodologies to tackle them. Our approach is to consider variants of classical combinatorial optimization problems belonging to three domains: packing, routing and integrated routing/packing. Our results suggest that indeed effective approaches exist, reducing the computational effort required for solving the problem. Mostly, they are based on exploiting the structure of optimal solutions to reduce the search space.