Mixed-integer linearity in nonlinear optimization: a trust region approach

Bringing together nonlinear optimization with mixed-integer linear constraints enables versatile modeling, but poses significant computational challenges. We investigate a method to solve these problems based on sequential mixed-integer linearization with trust region safeguard, computing feasible iterates via calls to a generic mixed-integer linear solver. Convergence to critical, possibly suboptimal, feasible points is established for arbitrary starting points. Finally, we present numerical applications in nonsmooth optimal control and optimal network design and operation.Comment: 17 pages, 3 figures, 2 table

Proximal Gradient Methods Beyond Monotony

We address composite optimization problems, which consist in minimizing the sum of a smooth and a merely lower semicontinuous function, without any convexity assumptions. Numerical solutions of these problems can be obtained by proximal gradient methods, which often rely on a line search procedure as globalization mechanism. We consider an adaptive nonmonotone proximal gradient scheme based on an averaged merit function and establish asymptotic convergence guarantees under weak assumptions, delivering results on par with the monotone strategy. Finally, we derive global worst-case rates for the iterates and a stationarity measure.Comment: 16 pages, 1 algorith

Local properties and augmented Lagrangians in fully nonconvex composite optimization

A broad class of optimization problems can be cast in composite form, that is, considering the minimization of the composition of a lower semicontinuous function with a differentiable mapping. This paper discusses the versatile template of composite optimization without any convexity assumptions. First- and second-order optimality conditions are discussed, advancing the variational analysis of compositions. We highlight the difficulties that stem from the lack of convexity when dealing with necessary conditions in a Lagrangian framework and when considering error bounds. Building upon these characterizations, a local convergence analysis is delineated for a recently developed augmented Lagrangian method, deriving rates of convergence in the fully nonconvex setting.Comment: 42 page

Self-Organised Schools

Self-Organised Schools: Educational Leadership and Innovative Learning Environments describes the results of the research we carried out at fourteen Italian schools that highlight how there is a positive correlation between the capabilities of school self-organization and the innovativeness of learning environments: in other words, the more self-organized schools are, the more innovative learning environments are. The results of this work are part of the strand of research of bottom-up emergency and self-organization, an extremely fruitful trend as shown by Sugata Mitra, the founder of the Self-Organized Learning Environments, according to whom, "education is a self-organized system where learning is an emerging phenomenon". This book gives new insights on self-organization studies, and most of all, to the idea that change - organizational and educational innovation - sparks from the bottom. This book is aimed specifically at school principals of all levels, scholastic reformers, educational scholars, organisation and management consultants who want to innovate learning and management of learning. These actors will benefit drawing useful examples from more than thirty different learning environments worldwide, fourteen examples of schools that self-organize, two frameworks - and two ready-to-use questionnaires - measuring the innovativeness of a learning environment, and the capability of a school to self-organize. Self-organization is the most fascinating future of innovative principal

Collision Avoidance using Iterative Dynamic and Nonlinear Programming with Adaptive Grid Refinements

Nonlinear optimal control problems for trajectory planning with obstacle avoidance present several challenges. While general-purpose optimizers and dynamic programming methods struggle when adopted separately, their combination enabled by a penalty approach was found capable of handling highly nonlinear systems while overcoming the curse of dimensionality. Nevertheless, using dynamic programming with a fixed state space discretization limits the set of reachable solutions, hindering convergence or requiring enormous memory resources for uniformly spaced grids. In this work we solve this issue by incorporating an adaptive refinement of the state space grid, splitting cells where needed to better capture the problem structure while requiring less discretization points overall. Numerical results on a space manipulator demonstrate the improved robustness and efficiency of the combined method with respect to the single components.Comment: Fixed typo in Reference [5

Gestire o nascondere i conflitti socio-ambientali? La Social Licence to Operate nelle attività petrolifere dell’Amazzonia ecuadoriana

The main objective of this research was to critically examine the concept of Social Licence to Operate (SLO) in an oil concession of the Ecuadorian Amazon inhabited by indigenous villages. In this paper we present the qualitative data of the semi-structured interviews and the household survey with village residents. The main findings revealed the important role of the involvement of communities in the decision-making processes (procedural fairness), people’s perceptions of company’s socio-environmental impacts, the management of forms of protest and social services in the communities. Particularly, the results suggested that procedural fairness and the respect of communities’ right of self-determination are the basic requisite for the application of the SLO concept in the study area

Formazione per il futuro: spunti di riflessione per il settore edile-artigianoA

Nota derivante dal lavoro svolto per il Progetto di ricerca Monitoraggio della formazione in materia di sicurezza e rilevazione delle competenze richieste, promosso da Edilcassa Veneto e svolto da Ires Veneto, consistente in focus group compiuto con le parti sociali

Cluster-based Vibration Analysis of Structures with GSP

This article describes a divide-and-conquer strategy suited for vibration monitoring applications. Based on a low-cost embedded network of microelectromechanical accelerometers, the proposed architecture strives to reduce both power consumption and computational resources. Moreover, it eases the sensor deployment on large structures by exploiting a novel clustering scheme, which consists of unconventional and nonoverlapped sensing configurations. Signal processing techniques for inter- and intracluster data assembly are introduced to allow for a fullscale assessment of the structural integrity. More specifically, the capability of graph signal processing is adopted for the first time in vibration-based monitoring scenarios to capture the spatial relationship between acceleration data. The experimental validation, conducted on a steel beam perturbed with additive mass, reveals high accuracy in damage detection tasks. Deviations in spectral content and mode shape envelopes are correctly revealed regardless of environmental factors and operational uncertainties. Furthermore, an additional key advantage of the implemented architecture relies on its compliance with blind modal investigations, an approach that favors the implementation of autonomous smart monitoring systems

Relativistic Digital Twin: Bringing the IoT to the Future

Complex IoT ecosystems often require the usage of Digital Twins (DTs) of their physical assets in order to perform predictive analytics and simulate what-if scenarios. DTs are able to replicate IoT devices and adapt over time to their behavioral changes. However, DTs in IoT are typically tailored to a specific use case, without the possibility to seamlessly adapt to different scenarios. Further, the fragmentation of IoT poses additional challenges on how to deploy DTs in heterogeneous scenarios characterized by the usage of multiple data formats and IoT network protocols. In this paper, we propose the Relativistic Digital Twin (RDT) framework, through which we automatically generate general-purpose DTs of IoT entities and tune their behavioral models over time by constantly observing their real counterparts. The framework relies on the object representation via the Web of Things (WoT), to offer a standardized interface to each of the IoT devices as well as to their DTs. To this purpose, we extended the W3C WoT standard in order to encompass the concept of behavioral model and define it in the Thing Description (TD) through a new vocabulary. Finally, we evaluated the RDT framework over two disjoint use cases to assess its correctness and learning performance, i.e., the DT of a simulated smart home scenario with the capability of forecasting the indoor temperature, and the DT of a real-world drone with the capability of forecasting its trajectory in an outdoor scenario.Comment: 17 pages, 10 figures, 4 tables, 6 listing

Unburnable and Unleakable Carbon in Western Amazon: Using VIIRS Nightfire Data to Map Gas Flaring and Policy Compliance in the Yasun\ued Biosphere Reserve

In the Amazon Rainforest, a unique post-carbon plan to mitigate global warming and to protect the exceptional bio-cultural diversity was experimented in 2007\u20132013 by the Ecuadorian government. To preserve the rainforest ecosystems within the Yasun\ued-ITT oil block, the release of 410 million metric tons of CO2 would have been avoided. The neologism \u201cyasunization\u201d emerged as an Amazonian narrative on \u201cunburnable carbon\u201d to be replicated worldwide. Considering the unburnable carbon, petroleum-associated gas flaring represents the unleakable part. Flaring is an irrational practice that consists of burning waste gases, representing not only a leak of energy but also a pollution source. The general aim of the paper is to monitor gas flaring as a tool, revealing, at the same time, the implementation of environmental technologies in the oil sector and the compliance of sustainable policies in the Amazon region and the Yasun\ued Biosphere Reserve. Specific objectives are: (i) identifying and estimating gas flaring over seven years (2012\u20132018); (ii) mapping new flaring sites; iii) estimating potentially affected areas among ecosystems and local communities. We processed National Oceanic and Atmospheric Administration (NOAA) Nightfire annual dataset, based on the elaboration of imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS) and developed a GIS-based novel simple method to identify new flaring sites from daily detections. We found that 23.5% of gas flaring sites and 18.4% of volumes of all oil industries operating in Ecuador are located within the Yasun\ued Biosphere Reserve (YBR). Moreover, we detected 34 additional flaring sites not included in the NOAA dataset\u201412 in the YBR and one in Tiputini field, a key area for biological and cultural diversity conservation. We also found that at least 10 indigenous communities, 18 populated centers and 10 schools are located in the potentially affected area. Gas flaring can be used as a policy indicator to monitor the implementation of sustainable development practices in complex territories