Università della Svizzera italiana

Advanced metaheuristics for the probabilistic orienteering problem

Chou, Xiaochen ; Gambardella, Luca Maria (Dir.) ; Montemanni, Roberto (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO020.

Stochastic Optimization Problems take uncertainty into account. For this reason they are in general more realistic than deterministic ones, meanwhile, more difficult to solve. The challenge is both on modelling and computation aspects: exact methods usually work only for small instances, besides, there are several problems with no closed-form expression or hard- to-compute objective functions....

Università della Svizzera italiana

Efficient combinatorial optimization algorithms for logistic problems

Papapanagiotou, Vasileios ; Gambardella, Luca Maria (Dir.) ; Montemanni, Roberto (Codir.) ; Schmidhuber, Jürgen (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2018 ; 2018INFO011.

The field of logistics and combinatorial optimization features a wealth of NP-hard problems that are of great practical importance. For this reason it is important that we have efficient algorithms to provide optimal or near-optimal solutions. In this work, we study, compare and develop Sampling-Based Metaheuristics and Exact Methods for logistic problems that are important for their...

Università della Svizzera italiana

Matheuristics for robust optimization : application to real-world problems

Toklu, Nihat Engin ; Gambardella, Luca Maria (Dir.) ; Montemanni, Roberto (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2014 ; 2014INFO008.

In the field of optimization, the perspective that the problem data are subject to uncertainty is gaining more and more interest. The uncertainty in an optimization problem represents the measurement errors during the phase of collecting data, or unforeseen changes in the environment while implementing the optimal solution in practice. When the uncertainty is ignored, an optimal solution...