Zobrazeno 1 - 10
of 181
pro vyhledávání: '"Massimo Paolucci"'
Autor:
Virginia Casella, Daniel Fernandez Valderrama, Giulio Ferro, Riccardo Minciardi, Massimo Paolucci, Luca Parodi, Michela Robba
Publikováno v:
Energies, Vol 15, Iss 11, p 4020 (2022)
In this paper, a survey is presented on the use of optimization models for the integration of electric vehicles (EVs) and charging stations (CSs) in the energy system, paying particular attention both to planning problems (i.e., those problems relate
Externí odkaz:
https://doaj.org/article/f7a759fc777b4fa8833988b15412e914
Publikováno v:
International Journal of Engineering Business Management, Vol 7 (2015)
This work presents a business intelligence tool for monitoring traffic accidents on motorways and supporting decisions relevant to road safety. The system manages information on road characteristics, traffic accidents and traffic volumes and produces
Externí odkaz:
https://doaj.org/article/e5737a6bbba442b6b1053674015fe72f
Autor:
Abdolreza Roshani, Massimo Paolucci, Davide Giglio, Melissa Demartini, Flavio Tonelli, Maxim A. Dulebenets
Publikováno v:
Annals of Operations Research. 321:469-505
Publikováno v:
IEEE Transactions on Automation Science and Engineering. 19:3-6
Publikováno v:
IEEE Transactions on Vehicular Technology. 69:14436-14447
In this article, a new mathematical formulation for the electric vehicle routing problem (EVRP) is proposed. This formulation extends the Green Vehicle Routing Problem (GVRP) considering time-of-use energy (TOU) prices, and including a detailed model
Autor:
Massimo Paolucci, Daniela Ambrosino
Publikováno v:
Networks. 78:227-228
Publikováno v:
Collaborative Logistics and Intermodality ISBN: 9783030509569
In this work an optimization approach for defining loading plans for trains in seaport container terminals is presented. The problem consists in defining the assignment of containers of different length, weight and value to wagon slots of a train, in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06fc0737de766d7a857af8c20a5c14c9
https://hdl.handle.net/11567/1057510
https://hdl.handle.net/11567/1057510
Autor:
Massimo Paolucci, Claudia Caballini
The evolving safety regulation is pushing seaports to comply with safety measures for workers performing heavy loads handling and repetitive movements. This paper proposes a risk-aware rostering approach in maritime container terminals, i.e., it addr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::541f485009b4e5554898585818478cb4
http://hdl.handle.net/11583/2833892
http://hdl.handle.net/11583/2833892
Publikováno v:
Soft computing (Berl., Print) (2020). doi:10.1007/s00500-020-05462-x
info:cnr-pdr/source/autori:Luca Caviglione, Mauro Gaggero, Massimo Paolucci, Roberto Ronco/titolo:Deep Reinforcement Learning for Multi-Objective Placement of Virtual Machines in Cloud Datacenters/doi:10.1007%2Fs00500-020-05462-x/rivista:Soft computing (Berl., Print)/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume
info:cnr-pdr/source/autori:Luca Caviglione, Mauro Gaggero, Massimo Paolucci, Roberto Ronco/titolo:Deep Reinforcement Learning for Multi-Objective Placement of Virtual Machines in Cloud Datacenters/doi:10.1007%2Fs00500-020-05462-x/rivista:Soft computing (Berl., Print)/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume
The ubiquitous diffusion of cloud computing requires suitable management policies to face the workload while guaranteeing quality constraints and mitigating costs. The typical trade-off is between the used power and the adherence to a service-level m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::698cbae660055d3725bfe5665318877a
https://hdl.handle.net/11567/1035752
https://hdl.handle.net/11567/1035752
Multi-sided assembly line balancing problems usually occur in plants producing big-sized products such as buses, trucks, and helicopters. In this type of assembly line, in each workstation, it is p...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::041612f26f1109f76efbef00b7be8c75
https://hdl.handle.net/11567/1005962
https://hdl.handle.net/11567/1005962