A mixed methods inquiry into the political economy of agriculture and rural areas in Lebanon

The present work, then, is concerned with the forgotten elements of the Lebanese economy, agriculture and rural development. It investigates the main problematic which arose from these forgotten components, in particular the structure of the agricultural sector, production technology, income distribution, poverty, food security, territorial development and local livelihood strategies. It will do so using quantitative Computable General Equilibrium (CGE) modeling and a qualitative phenomenological case study analysis, both embedded in a critical review of the historical development of the political economy of Lebanon, and a structural analysis of its economy. The research shows that under-development in Lebanese rural areas is not due to lack of resources, but rather is the consequence of political choices. It further suggests that agriculture – in both its mainstream conventional and its innovative locally initiated forms of production – still represents important potential for inducing economic growth and development. In order to do so, Lebanon has to take full advantage of its human and territorial capital, by developing a rural development strategy based on two parallel sets of actions: one directed toward the support of local rural development initiatives, and the other directed toward intensive form of production. In addition to its economic returns, such a strategy would promote social and political stability.

Development of Core Design Methods and Tools for Gen-IV Heavy Liquid Metal Cooled Reactors

Heavy Liquid Metal Cooled Reactors are among the concepts, fostered by the GIF, as potentially able to comply with stringent safety, economical, sustainability, proliferation resistance and physical protection requirements. The increasing interest around these innovative systems has highlighted the lack of tools specifically dedicated to their core design stage. The present PhD thesis summarizes the three years effort of, partially, closing the mentioned gap, by rationally defining the role of codes in core design and by creating a development methodology for core design-oriented codes (DOCs) and its subsequent application to the most needed design areas. The covered fields are, in particular, the fuel assembly thermal-hydraulics and the fuel pin thermo-mechanics. Regarding the former, following the established methodology, the sub-channel code ANTEO+ has been conceived. Initially restricted to the forced convection regime and subsequently extended to the mixed one, ANTEO+, via a thorough validation campaign, has been demonstrated a reliable tool for design applications. Concerning the fuel pin thermo-mechanics, the will to include safety-related considerations at the outset of the pin dimensioning process, has given birth to the safety-informed DOC TEMIDE. The proposed DOC development methodology has also been applied to TEMIDE; given the complex interdependence patterns among the numerous phenomena involved in an irradiated fuel pin, to optimize the code final structure, a sensitivity analysis has been performed, in the anticipated application domain. The development methodology has also been tested in the verification and validation phases; the latter, due to the low availability of experiments truly representative of TEMIDE's application domain, has only been a preliminary attempt to test TEMIDE's capabilities in fulfilling the DOC requirements upon which it has been built. In general, the capability of the proposed development methodology for DOCs in delivering tools helping the core designer in preliminary setting the system configuration has been proven.

La convivialità urbana nei quartieri di Milano, Bologna e Roma. Un'analisi mixed-methods sulle Social Streets

Le Social Street sono gruppi di vicini di casa che vogliono ricreare legami di convivialità avendo notato un indebolimento delle relazioni sociali nei loro quartieri. Nascono come gruppi online, tramite la piattaforma Facebook, per materializzarsi in incontri offline andando a costruire legami conviviali grazie pratiche di socialità, inclusività e gratuità. Questa Tesi ha come obiettivo l’analisi dei profili socio-demografici degli Streeter e dei quartieri coinvolti per comprendere come sia possibile creare convivialità e come la variabile urbana intervenga in questi processi. Inoltre, si vuole comprendere le dinamiche di attaccamento al quartiere, gli interessi portati avanti dagli Streeter, il loro profilo civico e il posizionamento di quest’esperienza rispetto all’associazionismo tradizionale. Per perseguire l’obiettivo della ricerca, sono state studiate le tre città che vedono la maggiore presenza di Social Street: Milano, Bologna, Roma. La ricerca ha previsto sia un’analisi degli Streeter grazie a un questionario online replicato in tutti i contesti. Inoltre, sono state realizzate 131 interviste ad amministratori e fondatori di Social Street e condotte osservazioni etnografiche e netnografiche. I risultati mostrano come gli Streeter siano appartenenti alle classi medio-alte, tra trenta e cinquanta anni, che hanno sperimentato la mobilità tra un quartiere e l’altro o tra diversi contesi nazionali ed internazionali e trovano nelle Social Street un modo per creare legami di vicinato che hanno perso nei loro trasferimenti. Gli stessi quartieri dove si diffondono le Social Street sono agiati e vi è una buona corrispondenza tra Streeter e modello della centralità sociale elaborato da Milbrath (1965) per cui anche la partecipazione civica è molto sentita tra gli aderenti alle Social Street. Il contributo di questa Tesi al dibattito sociologico risiede nell’aver offerto un’analisi empirica di un’azione collettiva a livello urbano, quella delle Social Street, mostrando come vi sia circolarità tra azione e contesto grazie all’azione mutualistica conviviale.

Application-oriented Mixed Integer Non-Linear Programming

In the most recent years there is a renovate interest for Mixed Integer Non-Linear Programming (MINLP) problems. This can be explained for different reasons: (i) the performance of solvers handling non-linear constraints was largely improved; (ii) the awareness that most of the applications from the real-world can be modeled as an MINLP problem; (iii) the challenging nature of this very general class of problems. It is well-known that MINLP problems are NP-hard because they are the generalization of MILP problems, which are NP-hard themselves. However, MINLPs are, in general, also hard to solve in practice. We address to non-convex MINLPs, i.e. having non-convex continuous relaxations: the presence of non-convexities in the model makes these problems usually even harder to solve. The aim of this Ph.D. thesis is to give a flavor of different possible approaches that one can study to attack MINLP problems with non-convexities, with a special attention to real-world problems. In Part 1 of the thesis we introduce the problem and present three special cases of general MINLPs and the most common methods used to solve them. These techniques play a fundamental role in the resolution of general MINLP problems. Then we describe algorithms addressing general MINLPs. Parts 2 and 3 contain the main contributions of the Ph.D. thesis. In particular, in Part 2 four different methods aimed at solving different classes of MINLP problems are presented. Part 3 of the thesis is devoted to real-world applications: two different problems and approaches to MINLPs are presented, namely Scheduling and Unit Commitment for Hydro-Plants and Water Network Design problems. The results show that each of these different methods has advantages and disadvantages. Thus, typically the method to be adopted to solve a real-world problem should be tailored on the characteristics, structure and size of the problem. Part 4 of the thesis consists of a brief review on tools commonly used for general MINLP problems, constituted an integral part of the development of this Ph.D. thesis (especially the use and development of open-source software). We present the main characteristics of solvers for each special case of MINLP.

Enhanced Mixed Integer Programming Techniques and Routing Problems

Mixed integer programming is up today one of the most widely used techniques for dealing with hard optimization problems. On the one side, many practical optimization problems arising from real-world applications (such as, e.g., scheduling, project planning, transportation, telecommunications, economics and finance, timetabling, etc) can be easily and effectively formulated as Mixed Integer linear Programs (MIPs). On the other hand, 50 and more years of intensive research has dramatically improved on the capability of the current generation of MIP solvers to tackle hard problems in practice. However, many questions are still open and not fully understood, and the mixed integer programming community is still more than active in trying to answer some of these questions. As a consequence, a huge number of papers are continuously developed and new intriguing questions arise every year. When dealing with MIPs, we have to distinguish between two different scenarios. The first one happens when we are asked to handle a general MIP and we cannot assume any special structure for the given problem. In this case, a Linear Programming (LP) relaxation and some integrality requirements are all we have for tackling the problem, and we are ``forced" to use some general purpose techniques. The second one happens when mixed integer programming is used to address a somehow structured problem. In this context, polyhedral analysis and other theoretical and practical considerations are typically exploited to devise some special purpose techniques. This thesis tries to give some insights in both the above mentioned situations. The first part of the work is focused on general purpose cutting planes, which are probably the key ingredient behind the success of the current generation of MIP solvers. Chapter 1 presents a quick overview of the main ingredients of a branch-and-cut algorithm, while Chapter 2 recalls some results from the literature in the context of disjunctive cuts and their connections with Gomory mixed integer cuts. Chapter 3 presents a theoretical and computational investigation of disjunctive cuts. In particular, we analyze the connections between different normalization conditions (i.e., conditions to truncate the cone associated with disjunctive cutting planes) and other crucial aspects as cut rank, cut density and cut strength. We give a theoretical characterization of weak rays of the disjunctive cone that lead to dominated cuts, and propose a practical method to possibly strengthen those cuts arising from such weak extremal solution. Further, we point out how redundant constraints can affect the quality of the generated disjunctive cuts, and discuss possible ways to cope with them. Finally, Chapter 4 presents some preliminary ideas in the context of multiple-row cuts. Very recently, a series of papers have brought the attention to the possibility of generating cuts using more than one row of the simplex tableau at a time. Several interesting theoretical results have been presented in this direction, often revisiting and recalling other important results discovered more than 40 years ago. However, is not clear at all how these results can be exploited in practice. As stated, the chapter is a still work-in-progress and simply presents a possible way for generating two-row cuts from the simplex tableau arising from lattice-free triangles and some preliminary computational results. The second part of the thesis is instead focused on the heuristic and exact exploitation of integer programming techniques for hard combinatorial optimization problems in the context of routing applications. Chapters 5 and 6 present an integer linear programming local search algorithm for Vehicle Routing Problems (VRPs). The overall procedure follows a general destroy-and-repair paradigm (i.e., the current solution is first randomly destroyed and then repaired in the attempt of finding a new improved solution) where a class of exponential neighborhoods are iteratively explored by heuristically solving an integer programming formulation through a general purpose MIP solver. Chapters 7 and 8 deal with exact branch-and-cut methods. Chapter 7 presents an extended formulation for the Traveling Salesman Problem with Time Windows (TSPTW), a generalization of the well known TSP where each node must be visited within a given time window. The polyhedral approaches proposed for this problem in the literature typically follow the one which has been proven to be extremely effective in the classical TSP context. Here we present an overall (quite) general idea which is based on a relaxed discretization of time windows. Such an idea leads to a stronger formulation and to stronger valid inequalities which are then separated within the classical branch-and-cut framework. Finally, Chapter 8 addresses the branch-and-cut in the context of Generalized Minimum Spanning Tree Problems (GMSTPs) (i.e., a class of NP-hard generalizations of the classical minimum spanning tree problem). In this chapter, we show how some basic ideas (and, in particular, the usage of general purpose cutting planes) can be useful to improve on branch-and-cut methods proposed in the literature.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

Geotechnical characterization of mixed sandy and silty soils using piezocone tests: Analysis of partial drainage phenomena and rate effects on the experimental soil response

The cone penetration test (CPT), together with its recent variation (CPTU), has become the most widely used in-situ testing technique for soil profiling and geotechnical characterization. The knowledge gained over the last decades on the interpretation procedures in sands and clays is certainly wide, whilst very few contributions can be found as regards the analysis of CPT(u) data in intermediate soils. Indeed, it is widely accepted that at the standard rate of penetration (v = 20 mm/s), drained penetration occurs in sands while undrained penetration occurs in clays. However, a problem arise when the available interpretation approaches are applied to cone measurements in silts, sandy silts, silty or clayey sands, since such intermediate geomaterials are often characterized by permeability values within the range in which partial drainage is very likely to occur. Hence, the application of the available and well-established interpretation procedures, developed for ‘standard’ clays and sands, may result in invalid estimates of soil parameters. This study aims at providing a better understanding on the interpretation of CPTU data in natural sand and silt mixtures, by taking into account two main aspects, as specified below: 1)Investigating the effect of penetration rate on piezocone measurements, with the aim of identifying drainage conditions when cone penetration is performed at a standard rate. This part of the thesis has been carried out with reference to a specific CPTU database recently collected in a liquefaction-prone area (Emilia-Romagna Region, Italy). 2)Providing a better insight into the interpretation of piezocone tests in the widely studied silty sediments of the Venetian lagoon (Italy). Research has focused on the calibration and verification of some site-specific correlations, with special reference to the estimate of compressibility parameters for the assessment of long-term settlements of the Venetian coastal defences.

Methods and tools to foster territorial approaches for the assessment of food supply chains

The challenges of the current global food systems are often framed around feeding the world's growing population while meeting sustainable development for future generations. Globalization has brought to a fragmentation of food spaces, leading to a flexible and mutable supply chain. This poses a major challenge to food and nutrition security, affecting also rural-urban dynamics in territories. Furthermore, the recent crises have highlighted the vulnerability to shocks and disruptions of the food systems and the eco-system due to the intensive management of natural, human and economic capital. Hence, a sustainable and resilient transition of the food systems is required through a multi-faceted approach that tackles the causes of unsustainability and promotes sustainable practices at all levels of the food system. In this respect, a territorial approach becomes a relevant entry point of analysis for the food system’s multifunctionality and can support the evaluation of sustainability by quantifying impacts associated with quantitative methods and understanding the territorial responsibility of different actors with qualitative ones. Against this background the present research aims to i) investigate the environmental, costing and social indicators suitable for a scoring system able to measure the integrated sustainability performance of food initiatives within the City/Region territorial context; ii) develop a territorial assessment framework to measure sustainability impacts of agricultural systems; and iii) define an integrated methodology to match production and consumption at a territorial level to foster a long-term vision of short food supply chains. From a methodological perspective, the research proposes a mixed quantitative and qualitative research method. The outcomes provide an in-depth view into the environmental and socio-economic impacts of food systems at the territorial level, investigating possible indicators, frameworks, and business strategies to foster their future sustainable development.