Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Gambella, Claudio"'
Autor:
Gambella, Claudio <1988>
In this thesis, we focus on mathematical optimization models and algorithms for solving routing and logistic problems. The first contribution regards a path and mission planning problem, called Carrier-Vehicle Traveling Salesman Problem (CVTSP), for
Externí odkaz:
http://amsdottorato.unibo.it/7607/
The Covid-19 pandemic introduces new challenges and constraints for return to work business planning. We describe a space allocation problem that incorporates social distancing constraints while optimising the number of available safe workspaces in a
Externí odkaz:
http://arxiv.org/abs/2105.05017
Autor:
Egger, Daniel J., Gambella, Claudio, Marecek, Jakub, McFaddin, Scott, Mevissen, Martin, Raymond, Rudy, Simonetto, Andrea, Woerner, Stefan, Yndurain, Elena
Publikováno v:
IEEE Transactions on Quantum Engineering, vol. 1, pp. 1-24, 2020, Art no. 3101724
This article outlines our point of view regarding the applicability, state-of-the-art, and potential of quantum computing for problems in finance. We provide an introduction to quantum computing as well as a survey on problem classes in finance that
Externí odkaz:
http://arxiv.org/abs/2006.14510
Autor:
Gambella, Claudio, Simonetto, Andrea
Publikováno v:
IEEE Transactions on Quantum Engineering 1 (2020)
Solving combinatorial optimization problems on current noisy quantum devices is currently being advocated for (and restricted to) binary polynomial optimization with equality constraints via quantum heuristic approaches. This is achieved using, e.g.,
Externí odkaz:
http://arxiv.org/abs/2001.02069
Autor:
Gambella, Claudio, Monteil, Julien, Dekusar, Anton, Barros, Sergio Cabrero, Simonetto, Andrea, Lassoued, Yassine
Publikováno v:
Transportation Letters, 1-7, 2019
The advent of on-demand mobility systems is expected to have a tremendous potential on the wellness of transportation users in cities. Yet such positive effects are reached when the systems under consideration enable seamless integration between data
Externí odkaz:
http://arxiv.org/abs/1912.00648
The transport literature is dense regarding short-term traffic predictions, up to the scale of 1 hour, yet less dense for long-term traffic predictions. The transport literature is also sparse when it comes to city-scale traffic predictions, mainly b
Externí odkaz:
http://arxiv.org/abs/1911.13042
Publikováno v:
57th Annual Allerton Conference on Communication, Control, and Computing (2019)
We study the projection onto the set of feasible inputs and the set of feasible solutions of a polynomial optimisation problem (POP). Our motivation is increasing the robustness of solvers for POP: Without a priori guarantees of feasibility of a part
Externí odkaz:
http://arxiv.org/abs/1909.07485
Publikováno v:
Transportation Research Part C: Emerging Technologies, vol. 108 (11), pages 269 - 288, 2019
Ridesharing has been emerging as a new type of mobility. However, the early promises of ridesharing for alleviating congestion in cities may be undermined by a number of challenges, including the growing number of proposed services and the subsequent
Externí odkaz:
http://arxiv.org/abs/1906.07567
Publikováno v:
Transportation Research Part C, vol. 101, pp. 208-232, April 2019
In this paper, we propose a novel, computational efficient, dynamic ridesharing algorithm. The beneficial computational properties of the algorithm arise from casting the ridesharing problem as a linear assignment problem between fleet vehicles and c
Externí odkaz:
http://arxiv.org/abs/1902.10676
Publikováno v:
European Journal of Operational Research, 290, May 2021
This paper surveys the machine learning literature and presents in an optimization framework several commonly used machine learning approaches. Particularly, mathematical optimization models are presented for regression, classification, clustering, d
Externí odkaz:
http://arxiv.org/abs/1901.05331