| OPTIMIZATION, DISCRETE MATHEMATICS AND APPLICATIONS (OPTIMA) |
ICT4SM ICT for sustainable mobility
Activity time range: 2012 Project leader: Giovanni Felici Source of funding: Ministry of Reserach Design and implementation of software and portals for the integration of meteo data, produced adopting the crowd sourcing paradigm or by running specific models and simulations, for intelligent and sustainable mobility applications MIE - Mobilita' Intelligente Ecosostenibile Activity time range: 2014 Project leader: Giuseppe Stecca Source of funding: Ministry of Reserach Il progetto MIE - Mobilità Intelligente Ecosostenibile ha l’obiettivo di definire le metodologie hardware / software, gli indicatori e le politiche di gestione della mobilità mirate alla minimizzazione dell’impatto ambientale e al miglioramento del servizio erogato agli utenti (tempi di percorrenza e dell’ottimizzazione dei consumi necessari per compiere gli spostamenti). Il progetto intende sviluppare un modello di gestione della mobilità, tramite un sistema di monitoraggio e controllo che sfrutti tecnologie innovative (sensori wireless a basso consumo energetico, applicazioni su smartphone, semafori intelligenti, varchi di controllo, accessi informatizzati per gestire in modo ottimizzato il traffico di persone e merci in situazioni di traffico ordinario o in situazioni straordinarie), e un sistema di supporto decisionale a sostegno di politiche per la mobilità intelligente, con modelli sui dati storici o sui dati in tempo reale. Progetto premiale MATHTECH Activity time range: 2012 Project leader: Giovanni Felici Source of funding: European Community Il progetto MATHTECH "La Matematica per la società e l'innovazione tecnologica" è basato sull'utilizzo di metodi matematici in alcuni degli ambiti di intervento prioritari per il paese e inseriti nel programma Horizon 2020. Tale progetto intende promuovere la massima interazione tra le discipline matematiche rappresentate nel CNR, e le esigenze di ricerca tecnologiche e sociali dell'industria e della società SIGMA - Sistema Integrato di sensori in ambiente cloud per la Gestione Multirischio Avanzata Activity time range: 2013 Project leader: Giuseppe Stecca Source of funding: Public Administration ll Sistema Integrato di sensori in ambiente cloud per la Gestione Multirischio Avanzata (SIGMA) è un’architettura multilivello che ha la funzione di acquisire, integrare ed elaborare dati eterogenei provenienti da diverse reti di sensori(meteo, sismiche, vulcaniche, idriche, pluviali, del traffico auto e navale, ambientali, video, ecc) con lo scopo di potenziare i sistemi di controllo e di monitoraggio sia ambientali che di produzione industriale per fornire dati utili alla prevenzione e gestione di situazioni di rischio tramite servizi erogati al cittadino ed alle imprese, sia pubbliche che private. Il sistema è progettato per consentirne l’utilizzo anche in aree e situazioni critiche nelle quali non siano disponibili le normali infrastrutture di comunicazione necessarie a veicolare i dati raccolti dalle reti di sensori. Project home pageUISH - URBAN INTELLIGENCE SCIENCE HUB FOR CITY NETWORK Activity time range: 2021 - 2024 Project leader: Giovanni Felici Source of funding: European Community Il progetto intende sviluppare un concetto innovativo di analisi digitale di realtà urbane complesse, mirato al supporto decisionale per la loro PIPER - Piattaforma Intelligente per l'Ottimizzazione delle operazioni di riciclo Activity time range: 2021 - 2023 Project leader: Giuseppe Stecca Source of funding: Public Administration PIPER - Piattaforma Intelligente per l'Ottimizzazione delle operazioni di riciclo Enti finanziatori: Comunità Europea e Regione Lazio
MINOA - Mixed Integer Nonlinear Optimization Applications Activity time range: 2018 - 2021 Project leader: Claudio Gentile Source of funding: European Community
Building upon the achievements of the Marie-Curie ITN Mixed-Integer Non-Linear Optimization (MINO) (2012 - 2016), the goal of the Mixed-Integer Non-Linear Optimisation Applications (MINOA) proposal is to train the next generation of highly qualified researchers and managers in applied mathematics, operations research and computer science that are able to face the modern imperative challenges of European and international relevance in areas such as energy, logistics, engineering, natural sciences, and data analytics. Twelve Early-Stage Researchers (ESRs) will be trained through an innovative training programme based on individual research projects motivated by these applications that due to their high complexity will stimulate new developments in the field. The mathematical challenges can neither be met by using a single optimisation method alone, nor isolated by single academic partners. Instead, MINOA aims at building bridges between different mathematical methodologies and at creating novel and effective algorithmic enhancements. As special challenges, the ESRs will work on dynamic aspects and optimisation in real time, optimisation under uncertainty, multilevel optimization and non-commutativity in quantum computing. The ESRs will devise new effective algorithms and computer implementations. They will validate their methods for the applications with respect to metrics that they will define. All ESRs will derive recommendations, both for optimised MINO applications and for the effectiveness of the novel methodologies. These ESRs belong to a new generation of highly-skilled researchers that will strengthen Europe'e human capital base in R&I in the fast growing field of mathematical optimisation. The ESR projects will be pursued in joint supervision between experienced practitioners from leading European industries and leading optimisation experts, covering a wide range of scientific fields (from mathematics to quantum computing and real-world applications). Grant Agreement 764759 — MINOA — H2020-MSCA-ITN-2017 Project home pagePRIN 2015 - Nonlinear and Combinatorial Aspects of Complex Networks Activity time range: 2017 - 2020 Project leader: Giovanni Rinaldi Source of funding: CNR "Networks are pervasive in our society" is the tagline to all research projects which deal with networks; this makes it no less true. From logistics to telecommunications, from energy to social interactions, many relevant phenomena in nature and society exhibit network structure. Hence, network-structured optimization has very many applications. Networks are a staple of combinatorial optimization. The network flow structure is present, either naturally or via clever reformulations, in the vast majority of hard combinatorial problems. The classical network flow constraints, via the integrality property, allow to model relevant combinatorial graph structures (paths, trees, cuts), and this can be exploited to devise clever algorithmic techniques for Mixed-Integer Linear problems (MILP) (e.g., reformulation, decomposition and polyhedral ones). Unfortunately, exploiting the network structure when nonlinearities are present, i.e. in Mixed-Integer NonLinear problems (MINLP), is far less obvious. It is not surprising, then, that nonlinear aspects of networks have traditionally been either approximated or downright ignored. Indeed, MINLPs have traditionally been shunned by researchers interested in solving real-life applications, due to the lack of solution approaches as efficient and reliable as those available for MILPs. Yet, real-world networks often exhibit crucial nonlinear aspects, related to, e.g.: - consumption or distribution of energy; - scheduling of resources at nodes/links; - transient (non steady-state) and time-dependent phenomena; - uncertainty about future network conditions; - multiple objective functions, e.g., independent actors influencing each other. Fortunately, during the last decade approaches for MINLPs have considerably progressed. Nowadays, MINLPs with carefully chosen nonlinearities can be solved with comparable efficiency to MILPs. We therefore believe it is time to deal with nonlinear aspects of networks. This project aims at exploiting, and further improving, the solid methodological background developed by the participating Research Units (RUs) to attack a host of relevant practical problems where the network structure is inextricably interwoven with nonlinear elements. As it often happens, models can be developed that capture analogous phenomena (e.g., congestion or resource scheduling) in apparently distant applications (e.g., logistics, energy and telecommunications), allowing to develop solution approaches that can be used to tackle several different practical problems. We therefore aim at factoring together the expertise of the RUs in both different application fields and algorithmic methodologies to construct a set of reference (both conceptual and software) tools that can be used to tackle several network-structured problems with nonlinear components, and therefore to improve the efficiency and effectiveness of solution approaches to many relevant real-world problems. PRIN 2015 - Smart PORt Terminals Activity time range: 2017 - 2020 Project leader: Giuseppe Stecca Source of funding: CNR The rapid evolution in sea world trade poses new and harder challenges to port authorities and operators. In particular: • the trend towards using larger vessels makes critical the available resource levels (time, space, manpower, equipment) asks for a smarter organization of them • the globalization of the industrial production systems suffers from regulations that need to be updated, also considering security issues • the development of Information and Communication Technologies, providing tools of larger capacity at decreasing cost, needs to be exploited in a smart way to find effective solutions. The objective of SPORT is to devise innovative and smart methodologies to design, implement, test and assess on the field an integrated and modular set of software elements able to provide a concrete support to the port logistics operators for the management of the intermodal activities. To reach this objective, the two-level approach of SPORT contemplates: • a common base with transversal integrated functions, such as communication and user interfaces, databases, base services, general modelling, optimization and simulation tools, etc. • an application level, with a series of modules, each dealing with a specific problem relevant for the port intermodal activity management in an integrated way. SPORT implements and tests a meaningful set of applications, for each of the operational areas of a port: • seaside: e.g., berthing operations, crane management • internal transport: e.g., tracing of materials within the terminal • gate operations: e.g., pre-clearing procedures, synchronization of truck arrivals • container operations management: e.g., stacking, re-shuffling • hinterland: e.g., drayage, dry-ports • human resources: e.g., staffing, rostering • impact: e.g., effect of large vessels, environment issues, relation with urban activities. Each area and application is developed with reference to one of seven of the major Italian ports: Trieste, Genova, Savona, Cagliari, Salerno, Gioia Tauro and Venezia. Furthermore, the same application is tested in several ports of the group. A distinguished character of SPORT is the strict involvement of field operators in the project, in order to first identify their needs and requirements and them to concretely test and validate the solutions proposed for the considered problems. To reach its goals, SPORT puts together the recognised knowledge and experience of seven Italian excellence research centres in Port Terminal Operations Management. For the first time, they all collaborate together and with authorities and operators in order to provide concrete answers to the challenges of port terminal operations management. Reverse Manufacturing Innovation Decision System (ReMInD) Activity time range: 2018 - 2020 Project leader: Giuseppe Stecca Source of funding: Public Administration The project REMIND - REverse Manufacturing INnovation Decision system has been granted by Regione Lazio! This 18 months project will address the optimization of reverse logistics and production planning for a manufacturing plants which produce plastic pellets from returned plastic goods. The project will digitalize the flow of material, helping to improve the monitoring and the control of the reverse logistics, and improve the quality of the production. CNR-IASI will develop innovative reverse distribution and production planning methods and algorithms.Call for proposals: POR FESR LAZIO 2014-2020. Public Notice "Circular Economy e Energia" INVESTIMENTO TOTALE DEL PROGETTO: € 105.591,41 Enti finanziatori: Comunità Europea e Regione Lazio ZED&L Zero Emission Distribution and Logistics Activity time range: 2018 - 2019 Project leader: Giuseppe Stecca Source of funding: Domestic private companies ZED&L (Zero Emissions Distribution & Logistics) proposes an innovative city logistic model for the shipment of products in urban areas. The project is aimed at the reduction of emissions, the noise, and the costs of the phyisical distribution. CNR-IASI is partner of the Zero Emission Distribution and Logistics project who recently won the prize Logistico dell’anno CNR-IASI will validate and analyse the performance of the distribution model. It will study also the differences, constraints, and opportunities offered by the distribution model under different configurations and against traditional models. CNR IASI developed the VALIDATION OF ZEDL system. The simulation tool can be used to analyse economical social and environmental performance of electric and traditional vehicle with different degree of integration with fotovoltaic systems for chargin. The tool can be used for research or academic purposes. If interested please send and email to giuseppe.stecca@iasi.cnr.it to receive it in excel format. Mixed-Integer Nonlinear Optimization: Approaches and Applications Activity time range: 2014 - 2017 Project leader: Claudio Gentile Source of funding: Ministry of Reserach Mathematical Optimization (MO) applied to Decision Making is nowadays, together with other disciplines like statistics and simulation, an established methodology for pursuing efficiency, reliability and safety in a variety of contexts such as (to mention but a few) energy production and distribution, smart mobility, and green technology. This is testified at the European Union level by the kick-off of the COST Action TD1207 "Mathematical Optimization in the Decision Support Systems for Efficient and Robust Energy Networks", within the ICT domain, which aims at fostering the tight collaboration among energy experts, decision makers, engineers and mathematicians to improve efficiency, safety and reliability of energy production and distribution. From a mathematical perspective, this success is due to the impressive progress within the decades of two specific research areas, namely Discrete Optimization (DO) and Nonlinear Programming (NLP). Almost in isolation from each other, DO and NLP have been able to successfully link methodological advances with software development, a process fostered and stimulated by the goal of solving real-world applications. These remarkable achievements are demonstrated by the variety of high-quality open-source software tools currently available and, simultaneously, by a handful of commercial software tools that compete, by closer and closer releases, on the exciting software market of optimization. The very last kick that is allowing MO to establish itself so firmly as a reference tool for Decision Making has been the final merge of DO and NLP. Indeed, many real-world applications require to simultaneously deal with discrete decisions (one unit is on or off, etc.) and nonlinear characteristics of the (physical) systems (energy-to-fuel conversion, etc.) giving rise to problems that would be totally intractable without specific algorithmic techniques derived within this unified framework currently known as Mixed-Integer Non Linear Programming (MINLP). This final merge is relatively recent with significant milestones as the successful joint research program between Carnegie Mellon University and IBM T.J. Watson Research in 2005 in the USA, the PRIN2009 "Integrated Approaches for Discrete and Non Linear Optimization" in Italy and the Marie-Curie ITN "Mixed-Integer Nonlinear Optimization" FP7-PEOPLE-ITN-2012 at the EU level. While the PRIN2009 project was still in the pioneering side of MINLP, trying to create solid connections between the two distinct communities and studying the links between the corresponding theoretical foundations, the current project aims at making a substantial step further, not only by integrating DO techniques within NLP and vice versa, but also by developing ad hoc algorithms and unified methodological frameworks. This will contribute to kick-starting the positive feedback loop between theoretical analysis and applications, with far-reaching consequences both on MO and on many applied fields. MINO - Mixed Integer Nonlinear Optimization (Marie Curie Initial Training Network) Activity time range: 2012 - 2016 Project leader: Claudio Gentile Source of funding: European Community Complex decision-making in enterprises should involve mathematical optimization methods, because a “best choice” has to be made out of a huge number of feasible options. A mathematical description of such decision processes typically involves both “continuous” and “discrete” decisions. If the latter are present, the customary modeling approach is to use integer variables, which are also used to represent all possible nonlinearities, so that the remaining part of the model is linear. This leads to Mixed-Integer Linear Optimization (MILO) problems, which can be handled nowadays by many packages, but are often very difficult to solve. CONTRAST Activity time range: 2013 - 2015 Project leader: Paolo Ventura Source of funding: Public Administration
Object of the CONTRAST project, developed together with Aresoft s.r.l., University of Genova, and University "La Sapienza" of Rome, has been the realization of a software package for managing some crucial logistic issues arising in the container yard of an intermodal transport hub. Such a software, usable via web by the station operators, allows an optimized management of the movements of containers and cranes within the yard, minimizing, at the same time, the number of reshuffle operations performed together with the total distance covered by the cranes. PRIN 2011 - Integrated Approaches for Discrete and Non Linear Optimization Activity time range: 2011 - 2013 Project leader: Claudio Gentile Source of funding: Ministry of Reserach The last 40 years have been living proof of a startling development of methodologies for integer and mixed integer linear programs (MILP). As a consequence many solvers for MILP were produced, both open-source and commercial. These are based on the latest theoretical results on MILP theory and they are being constantly updated. Even though the development of MILP techniques has not by far reached an end, the area of mixed integer non-liner programs (MINLP) is now a new frontier. To this area belong some classical optimization problems that can be regarded as an intersection of mixed integer linear (MILP) and continuous non-linear (NLP) problems. An important example is the Max-Cut problem which is particularly interesting from a theoretical point of view as well as practical, and has been MOTUS Activity time range: 2008 - 2010 Project leader: Giovanni Felici Source of funding: CNR MOTUS is a project financed by INDUSTRIA 2015 and led by Telecom Italia. Its purpose is to develop new tools for info mobility based on new technologies among which new methods to track cellular phone traffic to support vehicle and pedestrian mobility in 6 main Italian cities. The main focus of the project are tourist flows, that will be oriented and guided through the many options offered by the main artistic Italian cities. The project is developed by a large team of research institutes and laboratories (from CNR and Universities) and several private companies. FLEETS Activity time range: 2008 - 2009 Project leader: Giovanni Felici Source of funding: Domestic private companies Development of a Planning and Optimization of Fleets system that manages the whole life cycle of the vehicles, from planning to disposal, including both Statutory and Managerial Accounting fulfillments. Project home pagePROGESOFT Activity time range: 2008 - 2009 Project leader: Giovanni Felici Source of funding: CNR Progetto di trasferimento tecnologico per la formulazione tramite programmazione matematica di problemi di ottimizzazione di flotte di veicoli per società di car renta ADONET-Algorithm Discrete Optimization Network Activity time range: 2004 - 2008 Project leader: Giovanni Rinaldi Source of funding: European Community Increasing international competition on all markets steadily puts further requirements on productivity, product quality and environmental compatibility for companies operating in Europe. In order to meet these challenging requirements, it is important to use mathematical tools in practice. In fact, many of the design and planning problems arising in practice involve decisions that ought to be taken in an optimal way. Since decisions can only be taken or not, models from discrete mathematics are a natural framework to attach such questions. Finding the optimal soultion of the mathematical model requires the development of algorithms from discrete mathematics that are high complex, and hence, can only be designed by a network of scientists with great expertise in this domain. The research objective of this network activity is to advance our ability to solve practical optimization problems. This requires the design of novel algorithms for a variety of discrete models that are based on the solution of structural and algoritmic questions in the area of integer programming, convex programming and combinatorial optimization. The partners of the project are the following: University of Magdeburg (Germany) , Catholique University of Louvain - CORE (Belgium), CWI-Amsterdam (The Netherlands), National Research Council of Italy, Institute for System Analysis and Computer Science "A. Ruberti" (Italy), Institut National Polytechnique de Grenoble (France), Federal Institute of Technology of Lausanne (Switzerland), University of Lisbon (Portugal), Dash Optimization (UK), Vienna University of Technology (Austria), Eotvos Lorand University Budapest (Hungary). CODESNET Activity time range: 2005 - 2008 Project leader: Bielli M. Source of funding: European Community Collaborative enterprises network. This coordination action was designed to promote the diffusion of the European scientific knowledge on the problem of designing and managing large-scale multi-functional multi-agents collaborative demand & supply networks of production, logistics and service enterprises operating within a common industrial sector. Main activities carried out consist of setting up a common information system with tools, procedures, performance evaluations and best practices in supply and logistics fields. In particular, a Virtual Library was organised in order to collect scientific papers and solution procedures. Then, a Virtual Laboratory provides a benchmark of enterprises clusters in Europe, by presenting an aggregate analysis of their financial, economic, operational structure, the organizational issues, the interactions with the socio-economic environment and the expected development. One of the key contributions is the identification of a number of performances indicators specific for this context. Project home pageFIRB 2005 - Interazione tra regolazione semaforica ed equilibrio di flussi di traffico nelle reti stradali Activity time range: 2005 - 2008 Project leader: Giovanni Felici Source of funding: Ministry of Reserach The object of the research was to develop a general framework for study, model and solve the problem of optimal road network signal settings, by taking into account the interaction between signal control systems and traffic flow patterns. Therefore, the research has been focused on modelling traffic flows along coordinated arteries and urban networks, on the integration of signal control and dynamic traffic assignment, on advanced models and methods for traffic signal setting and traffic control strategies. TMS Activity time range: 2006 - 2008 Project leader: Giovanni Felici Source of funding: CNR Design of a innovative transmission system of a surface propeller for leisure boats; analysis, design and development of the automatic control algorithm of trims and flaps of the transmission system; design and development of an automatic system for the optimization of navigation comfort. Project home pageFIRB Activity time range: 2003 - 2004 Project leader: De Simone C. Source of funding: Ministry of Reserach Graph colouring problems AGENZIA 2000 Activity time range: 2000 - 2003 Project leader: Claudio Gentile Source of funding: CNR Optimization Models and Algorithms for the Production and Distribution of Power Energy in the Free Market (subproject Polyhedral Methods for Problems arising in Production and Distribution of Power Energy): Polyhedral methods for Mixed Integer Non Linear Programming. Solution Algorithms for Unit Commitment problems. Models and Algorithms for the design of Bidding Strategies. Dynamic Programming algorithms for ramp constrained Unit Commitment problems.
AGENZIA 2000 Activity time range: 2001 - 2003 Project leader: Anna Galluccio Source of funding: CNR Algorithms to design and maintain survivable communication networks Project home pageDONET Activity time range: 2000 - 2003 Project leader: Giovanni Rinaldi Source of funding: European Community Discrete Optimization Network SORSA - Network Simulation and Optimization: Software and Applications Activity time range: 2002 - 2003 Project leader: Giovanni Rinaldi Source of funding: Ministry of Reserach The project concerns the study of new design and management network problems in production and in public services. In particular, the target is to develop new and more efficient simulation and optimization network algorithms both at a local and at a national scale. Two specific fields of application will be addressed: telecommunication networks (in cooperation with Telecom Italia) and transportation networks (in cooperation with Ferrovie dello Stato and Alitalia). Another target, to be pursued in parallel, is to conceive and create a data base of standardized and documented software for the solution of simulation and optimization problems on networks. The software collection will be made available, also after the project end, to the scientific community as well as to private and public companies, and to the public administration. The subproject consists of three research actions:
HCHLOUSO - Hydrocarbon and chemical logistics optimization under uncertainty via stochastic optimization Activity time range: 1997 - 2000 Project leader: Giovanni Felici Source of funding: European Community The ability to solve large (in terms of the number of decision variables) and stochastic (in terms of parameters whose values cannot be controlled by the decision maker and are uncertain) industrial problems in practice depends on the sophistication of the tools and techniques available. The project will remedy the inadequacies of the tools currently available by developing flexible software for Supply, Transformation and Distribution (STD) logistics scheduling under uncertainty with access to new, more powerful methods capable of solving problems currently considered intractable. Specifically, the project aims to confer the ability to solve vital revenue critical problems for the industrial partners, namely, STD logistics scheduling under uncertainty for the Hydrocarbon and Chemical sector. |
| - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
