In: Algorithms, 2021, vol. 14, no. 9, p. 25
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...
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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....
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO004.
Human-robot interaction (HRI) is an active area of research and an essential component for the effective integration of mobile robots in everyday environments. In this PhD work, we studied, designed, implemented, and experimentally validated new efficient interaction modalities between humans and robots that share the same workspace. The core of the work revolves around deictic (pointing)...
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Thèse de doctorat : Università della Svizzera italiana, 2018 ; 2018INFO010.
Autonomous robots in real-world environments face a number of challenges even to accomplish apparently simple tasks like moving to a given location. We present four realistic scenarios in which robot navigation takes into account partial information, hierarchical structures, and multiple objectives. We start by discussing navigation in indoor environments shared with people, where routes are...
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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...
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In: 4OR, 2005, vol. 3, no. 4, p. 315-328
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In: Natural Computing, 2009, vol. 8, no. 2, p. 239-287
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Thèse de doctorat : Università della Svizzera italiana, 2017 ; 2017INFO014.
With the advent of cloud computing, applications are no longer tied to a single device, but they can be migrated to a high-performance machine located in a distant data center. The key advantage is the enhancement of performance and consequently, the users experience. This activity is commonly referred computational offloading and it has been strenuously investigated in the past years. The...
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Thèse de doctorat : Università della Svizzera italiana, 2016 ; 2016INFO003.
Comprising of a potentially large team of autonomous cooperative robots locally interacting and communicating with each other, robot swarms provide a natural diversity of parallel and distributed functionalities, high flexibility, potential for redundancy, and fault-tolerance. The use of autonomous mobile robots is expected to increase in the future and swarm robotic systems are envisioned to...
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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...
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