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3 Annals of Computer Science and Information Systems

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Solving Assignment Problems via Quantum Computing: a Case-Study in Train Seating Arrangement

Gioda Ilaria, Caputo Davide, Fadda Edoardo, Manerba Daniele, Silva Fernández Blanca, Tadei Roberto

Annals of Computer Science and Information Systems

2021

Vol. 25

217--220

In recent years, researchers have oriented their studies towards new technologies based on quantum physics that should resolve complex problems currently considered to be intractable. This new research area is called Quantum Computing. What makes Quantum Computing so attractive is the particular way with which quantum technology operates and the great potential it can offer to solve real-world problems. This work focuses on solving assignment-like combinatorial optimization problems by exploiting this novel computational approach. A case-study, denoted as the Seating Arrangement Optimization problem, is considered. It is modeled through the Quadratic Unconstrained Binary Optimization paradigm and solved through two tools made available by the D-Wave Systems company, QBSolv, and a quantum-classical hybrid system. The obtained experimental results are compared in terms of solution quality and computational efficiency

Reinforcement Learning Algorithms for Online Single-Machine Scheduling

Li Yuanyuan, Fadda Edoardo, Manerba Daniele, Tadei Roberto, Terzo Olivier

Annals of Computer Science and Information Systems

2020

Vol. 21

277--283

Online scheduling has been an attractive field of research for over three decades. Some recent developments suggest that Reinforcement Learning (RL) techniques have the potential to deal with online scheduling issues effectively. Driven by an industrial application, in this paper we apply four of the most important RL techniques, namely Q-learning, Sarsa, Watkins's Q(λ), and Sarsa(λ), to the online single-machine scheduling problem. Our main goal is to provide insights on how such techniques perform. The numerical results show that Watkins's Q(λ) performs best in minimizing the total tardiness of the scheduling process.

KPIs for optimal location of charging stations for electric vehicles: the Biella case-study

Fadda Edoardo, Manerba Daniele, Cabodi Gianpiero, Camurati Paolo, Tadei Roberto

Annals of Computer Science and Information Systems

2019

Vol. 18

123--126

Electric vehicles are accelerating the world's transition to sustainable energy. Nevertheless, the lack of a proper charging station infrastructure in many real implementations still represents an obstacle for the spread of such a technology. In this paper, we present a real case application of optimization techniques in order to solve the location problem of electric charging stations in the district of Biella, Italy. The plan is composed by several progressive installations and decision makers pursue several objectives that might be in contrast. For this reason, we present an innovative framework based on the comparison of several ad-hoc Key Performance Indicators for evaluating many different aspects of a location solution.