New coding scheme to compile circuits for Quantum Approximate Optimization Algorithm by genetic evolution

Autor: Lis Arufe, Riccardo Rasconi, Angelo Oddi, Ramiro Varela, Miguel A. González

Publikováno v: Applied Soft Computing. :110456

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::37af0cb694ee050d3de1a8276cb1f258
https://doi.org/10.1016/j.asoc.2023.110456

Compiling Single Round QCCP-X Quantum Circuits by Genetic Algorithm

Autor: Lis Arufe, Riccardo Rasconi, Angelo Oddi, Ramiro Varela, Miguel Ángel González

Publikováno v: Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence ISBN: 9783031065262

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::82bd287b408dcef7ad1f6d9424423ec2
https://doi.org/10.1007/978-3-031-06527-9_9

An Innovative Genetic Algorithm for the Quantum Circuit Compilation Problem

Autor: Angelo Oddi, Riccardo Rasconi

Publikováno v: AAAI

Quantum Computing represents the next big step towards speed boost in computation, which promises major breakthroughs in several disciplines including Artificial Intelligence. This paper investigates the performance of a genetic algorithm to optimize

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d2071def5044f622e9fa37ba2fdf7763
https://doi.org/10.1609/aaai.v33i01.33017707

Knowledge Based Modules for Adaptive Distributed Control Systems

Autor: Andrea Orlandini, Ivan Cibrario Bertolotti, Alessandro Brusaferri, Andrea Ballarino, Amedeo Cesta, Luca Durante, Guido Chizzoli, Riccardo Rasconi, Adriano Valenzano, Stefano Spinelli

Publikováno v: Factories of the Future ISBN: 9783319943572
FACTORIES OF THE FUTURE: THE ITALIAN FLAGSHIP INITIATIVE, edited by Tolio T., Copani G., Terkaj W., pp. 83–108. Cham, Heidelberg, New York, Dordrecht, London: Springer, 2019
info:cnr-pdr/source/autori:Ballarino, Andrea; Brusaferri, Alessandro; Cesta, Amedeo; Chizzoli, Guido; Bertolotti, Ivan Cibrario; Durante, Luca; Orlandini, Andrea; Rasconi, Riccardo; Spinelli, Stefano; Valenzano, Adriano/titolo:Knowledge Based Modules for Adaptive Distributed Control Systems/titolo_volume:FACTORIES OF THE FUTURE: THE ITALIAN FLAGSHIP INITIATIVE/curatori_volume:Tolio T., Copani G., Terkaj W./editore: /anno:2019

Modern automation systems are asked to provide a step change toward flexibility and reconfigurability to cope with increasing demand for fast changing and highly fragmented production--which is more and more characterising the manufacturing sector. T

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dad833f818e26bfc5869cf0197b1c855
https://doi.org/10.1007/978-3-319-94358-9_4

Energy-Aware Multiple State Machine Scheduling for Multiobjective Optimization

Autor: Riccardo Rasconi, Miguel A. González, Angelo Oddi

Publikováno v: AI*IA 2018 – Advances in Artificial Intelligence ISBN: 9783030038397
AI*IA
XVIIth International Conference of the Italian Association for Artificial Intelligence, pp. 474–486, Trento, Italy, November 20-23, 2018
info:cnr-pdr/source/autori:Oddi, Angelo; Rasconi, Riccardo; Gonzalez, Miguel A./congresso_nome:XVIIth International Conference of the Italian Association for Artificial Intelligence/congresso_luogo:Trento, Italy/congresso_data:November 20-23, 2018/anno:2018/pagina_da:474/pagina_a:486/intervallo_pagine:474–486

Optimising the energy consumption is one of the most important issues in scheduling nowadays. In this work we consider a multi-objective optimisation for the well-known job-shop scheduling problem. In particular, we minimise the makespan and the ener

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4ad14e3269befd490d7efe10fe1b0c2
https://doi.org/10.1007/978-3-030-03840-3_35