A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

Towards the stabilization of the low density elements in topology optimization with large deformation

This work addresses the treatment of lower density regions of structures undergoing large deformations during the design process by the topology optimization method (TOM) based on the finite element method. During the design process the nonlinear elastic behavior of the structure is based on exact kinematics. The material model applied in the TOM is based on the solid isotropic microstructure with penalization approach. No void elements are deleted and all internal forces of the nodes surrounding the void elements are considered during the nonlinear equilibrium solution. The distribution of design variables is solved through the method of moving asymptotes, in which the sensitivity of the objective function is obtained directly. In addition, a continuation function and a nonlinear projection function are invoked to obtain a checkerboard free and mesh independent design. 2D examples with both plane strain and plane stress conditions hypothesis are presented and compared. The problem of instability is overcome by adopting a polyconvex constitutive model in conjunction with a suggested relaxation function to stabilize the excessive distorted elements. The exact tangent stiffness matrix is used. The optimal topology results are compared to the results obtained by using the classical Saint Venant–Kirchhoff constitutive law, and strong differences are found.

Design methodology of piezoelectric energy-harvesting skin using topology optimization

Abstract This paper describes a design methodology for piezoelectric energy harvester s that thinly encapsulate the mechanical devices and expl oit resonances from higher- order vibrational modes. The direction of polarization determines the sign of the pi ezoelectric tensor to avoid cancellations of electric fields from opposite polarizations in the same circuit. The resultant modified equations of state are solved by finite element method (FEM). Com- bining this method with the solid isotropic material with penalization (SIMP) method for piezoelectric material, we have developed an optimization methodology that optimizes the piezoelectric material layout and polarization direc- tion. Updating the density function of the SIMP method is performed based on sensitivity analysis, the sequen- tial linear programming on the early stage of the opti- mization, and the phase field method on the latter stage

Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation

Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, traditional decision-tree induction algorithms implement a greedy approach for node splitting that is inherently susceptible to local optima convergence. Evolutionary algorithms can avoid the problems associated with a greedy search and have been successfully employed to the induction of decision trees. Previously, we proposed a lexicographic multi-objective genetic algorithm for decision-tree induction, named LEGAL-Tree. In this work, we propose extending this approach substantially, particularly w.r.t. two important evolutionary aspects: the initialization of the population and the fitness function. We carry out a comprehensive set of experiments to validate our extended algorithm. The experimental results suggest that it is able to outperform both traditional algorithms for decision-tree induction and another evolutionary algorithm in a variety of application domains.

Synthesis and properties of substituted Hg-based superconductors

This thesis is focused on studies of substituted Hg-based superconducting copper oxides ((Hg1-xMx)Ba2Can-1CunO2n+2+δ). These compounds are promising objects of investigation, not only from a fundamental point of view but also because of their high values of superconducting transition temperature (Tc) and irreversibility field (Hirr). The first part of the thesis is devoted to optimization of the synthesis procedure for Hg-based cuprates. The influence of different parameters (T, t, p(Hg), p(O2)) on the synthesis of these compounds in sealed silica tubes was studied. Optimal conditions yielded samples containing up to 95% of HgBa2Ca2Cu3O8+δ (Hg-1223). The formation of solid solutions with the formula (Hg1-xCux)Ba2Ca2Cu3O8+δ (where x <= 0.5) was also established. Another technique was developed, using LiF as a flux, for synthesis of samples containing up to 90% of the HgBa2CaCu2O6+δ (Hg-1212) phase. The second part concerns synthesis and studies of oxyfluorides using Hg-1212 and Hg-1223 as starting materials together with XeF2 as a fluorinating agent. It was found that oxyfluorides of both phases have a parabolic dependence of Tc vs. a parameter as well as enhanced Tc values (ΔT ≈ 3-4 K) in comparison with optimally doped non-fluorinated analogues. The crystal structure of Hg-1223 oxyfluoride was studied by X-ray powder and neutron diffraction methods. It is suggested that chemical modification of the crystal structure leads to a decrease in Cu-O distance without noticeable change in Cu-O-Cu angle (in the (CuO2) layers), which may be the significant factors influencing this Tc increase. Hg-1223 oxyfluoride was also studied under high pressure for first time. It was found that this compound has a record-high Tc value (≈ 166 K) at P ≈ 23 GPa. The last part describes the investigation of substituted Hg-based superconductors in the series (Hg0.9M0.1)Ba2CuO4+δ {(Hg,M)-1201}, where M = Tl, Pb, W, Mo, Nb and V. A comprehensive study of these compounds by various methods (X-ray powder diffraction, EDX, IR-, EXAFS- and XANES -spectroscopy) indicated that the change of charge carrier doping level is a crucial factor determining the irreversibility line. (Hg0.9Mo0.1)Ba2CuO4+δ showed the most improved irreversibility line position among the (Hg,M)-1201 compounds studied in this series.

Performance Optimization of a Floating Breakwater Model Using SPH Method, with a Practical Application

Máster en Oceanografía

Structural analysis of combinatorial optimization problem characteristics and their resolution using hybrid approaches

Many combinatorial problems coming from the real world may not have a clear and well defined structure, typically being dirtied by side constraints, or being composed of two or more sub-problems, usually not disjoint. Such problems are not suitable to be solved with pure approaches based on a single programming paradigm, because a paradigm that can effectively face a problem characteristic may behave inefficiently when facing other characteristics. In these cases, modelling the problem using different programming techniques, trying to ”take the best” from each technique, can produce solvers that largely dominate pure approaches. We demonstrate the effectiveness of hybridization and we discuss about different hybridization techniques by analyzing two classes of problems with particular structures, exploiting Constraint Programming and Integer Linear Programming solving tools and Algorithm Portfolios and Logic Based Benders Decomposition as integration and hybridization frameworks.

Improved ground motion intensity measures for reliability-based demand analysis of structures

In Performance-Based Earthquake Engineering (PBEE), evaluating the seismic performance (or seismic risk) of a structure at a designed site has gained major attention, especially in the past decade. One of the objectives in PBEE is to quantify the seismic reliability of a structure (due to the future random earthquakes) at a site. For that purpose, Probabilistic Seismic Demand Analysis (PSDA) is utilized as a tool to estimate the Mean Annual Frequency (MAF) of exceeding a specified value of a structural Engineering Demand Parameter (EDP). This dissertation focuses mainly on applying an average of a certain number of spectral acceleration ordinates in a certain interval of periods, Sa,avg (T1,…,Tn), as scalar ground motion Intensity Measure (IM) when assessing the seismic performance of inelastic structures. Since the interval of periods where computing Sa,avg is related to the more or less influence of higher vibration modes on the inelastic response, it is appropriate to speak about improved IMs. The results using these improved IMs are compared with a conventional elastic-based scalar IMs (e.g., pseudo spectral acceleration, Sa ( T(¹)), or peak ground acceleration, PGA) and the advanced inelastic-based scalar IM (i.e., inelastic spectral displacement, Sdi). The advantages of applying improved IMs are: (i ) "computability" of the seismic hazard according to traditional Probabilistic Seismic Hazard Analysis (PSHA), because ground motion prediction models are already available for Sa (Ti), and hence it is possibile to employ existing models to assess hazard in terms of Sa,avg, and (ii ) "efficiency" or smaller variability of structural response, which was minimized to assess the optimal range to compute Sa,avg. More work is needed to assess also "sufficiency" and "scaling robustness" desirable properties, which are disregarded in this dissertation. However, for ordinary records (i.e., with no pulse like effects), using the improved IMs is found to be more accurate than using the elastic- and inelastic-based IMs. For structural demands that are dominated by the first mode of vibration, using Sa,avg can be negligible relative to the conventionally-used Sa (T(¹)) and the advanced Sdi. For structural demands with sign.cant higher-mode contribution, an improved scalar IM that incorporates higher modes needs to be utilized. In order to fully understand the influence of the IM on the seismis risk, a simplified closed-form expression for the probability of exceeding a limit state capacity was chosen as a reliability measure under seismic excitations and implemented for Reinforced Concrete (RC) frame structures. This closed-form expression is partuclarly useful for seismic assessment and design of structures, taking into account the uncertainty in the generic variables, structural "demand" and "capacity" as well as the uncertainty in seismic excitations. The assumed framework employs nonlinear Incremental Dynamic Analysis (IDA) procedures in order to estimate variability in the response of the structure (demand) to seismic excitations, conditioned to IM. The estimation of the seismic risk using the simplified closed-form expression is affected by IM, because the final seismic risk is not constant, but with the same order of magnitude. Possible reasons concern the non-linear model assumed, or the insufficiency of the selected IM. Since it is impossibile to state what is the "real" probability of exceeding a limit state looking the total risk, the only way is represented by the optimization of the desirable properties of an IM.

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.

Homeostatic Patterns - Processi biomimetici feedback-based per una architettura efficiente nei Prati di Caprara

Gli organismi biologici mostrano ricorrenti dinamiche di auto-organizzazione nei processi morfogenetici che sono alla base di come la materia acquisisce gerarchia e organizzazione.L’omeostasi è la condizione con la quale un corpo raggiunge il proprio equilibrio (termico, pressione, ecc.); un processo attraverso il quale questi sistemi stabilzzano le reazioni fisiologiche. Una delle caratteristiche fondamentali esibite da tali organismi è la capacità della materia di instaurare processi di auto-organizzazione, responsabile dei processi di ottimizzazione che guidano all’uso efficiente dell’energia nella lotta per la sopravvivenza. Questa ottimizzazione non mira al raggiungimento di un risultato globale deterministico e “chiuso” (precedentemente stabilito e poi perseguito ad ogni costo), quanto piuttosto al raggiungimento di un’efficienza di processi locali con obiettivi multipli e necessità divergenti; tali processi interagiscono organizzando sistemi nei quali proprietà peculiari uniche emergono dalle interazioni descritte. Le esigenze divergenti non sono negoziate sulla base di un principio di esclusività (una esigenza esclude o elimina le altre) ma da un principio di prevalenza, dove le necessità non prevalenti non cessano di esistere ma si modificano in funzione di quelle prevalenti (il proprio campo di espressione è vincolato dai percorsi tracciati in quello delle esigenze prevalenti). In questa tesi si descrive un’applicazione ad uno specifico caso di studio di progettazione architettonica: un parco con spazi polifunzionali nella città di Bologna. L’obiettivo principale del progetto Homeostatic Pattern è quello di dimostrare come questo tipo di processi possano essere osservati, compresi e traslati in architettura: come per gli organismi biologici, in questo progetto gli scambi di materia ed energia (stabilità, respirazione, porosità alla luce) sono regolati da sistemi integrati efficienti piuttosto che da raggruppamenti di elementi mono-ottimizzati. Una specifica pipeline di software è stata costituita allo scopo di collegare in modo bidirezionale e senza soluzione di continuità un software di progettazione parametrica generativa (Grasshopper®) con software di analisi strutturale ed ambientale (GSA Oasys®, Autodesk® Ecotect® analysis), riconducendo i dati nella stessa struttura attraverso cicli di feedback. Il sistema così ottenuto mostra caratteristiche sia a scala macroscopica, come la possibilità di utilizzo della superficie esterna che permette anche un’estensione dell’area verde (grazie alla continuità della membrana), sia alla scala del componente, come la propria capacità di negoziare, tra le altre, la radiazione solare e la modulazione della luce, così come la raccolta capillare delle acque meteoriche. Un sistema multiperformante che come tale non persegue l’ottimizzazione di una singola proprietà ma un miglioramento complessivo per una maggiore efficienza.

An evolutionary approach to the design of experiments for combinatorial optimization with an application to enzyme engineering

In a large number of problems the high dimensionality of the search space, the vast number of variables and the economical constrains limit the ability of classical techniques to reach the optimum of a function, known or unknown. In this thesis we investigate the possibility to combine approaches from advanced statistics and optimization algorithms in such a way to better explore the combinatorial search space and to increase the performance of the approaches. To this purpose we propose two methods: (i) Model Based Ant Colony Design and (ii) Naïve Bayes Ant Colony Optimization. We test the performance of the two proposed solutions on a simulation study and we apply the novel techniques on an appplication in the field of Enzyme Engineering and Design.

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.

Physical models for numerical simulation of Si-based nanoscale FETs and sensors

To continuously improve the performance of metal-oxide-semiconductor field-effect-transistors (MOSFETs), innovative device architectures, gate stack engineering and mobility enhancement techniques are under investigation. In this framework, new physics-based models for Technology Computer-Aided-Design (TCAD) simulation tools are needed to accurately predict the performance of upcoming nanoscale devices and to provide guidelines for their optimization. In this thesis, advanced physically-based mobility models for ultrathin body (UTB) devices with either planar or vertical architectures such as single-gate silicon-on-insulator (SOI) field-effect transistors (FETs), double-gate FETs, FinFETs and silicon nanowire FETs, integrating strain technology and high-κ gate stacks are presented. The effective mobility of the two-dimensional electron/hole gas in a UTB FETs channel is calculated taking into account its tensorial nature and the quantization effects. All the scattering events relevant for thin silicon films and for high-κ dielectrics and metal gates have been addressed and modeled for UTB FETs on differently oriented substrates. The effects of mechanical stress on (100) and (110) silicon band structures have been modeled for a generic stress configuration. Performance will also derive from heterogeneity, coming from the increasing diversity of functions integrated on complementary metal-oxide-semiconductor (CMOS) platforms. For example, new architectural concepts are of interest not only to extend the FET scaling process, but also to develop innovative sensor applications. Benefiting from properties like large surface-to-volume ratio and extreme sensitivity to surface modifications, silicon-nanowire-based sensors are gaining special attention in research. In this thesis, a comprehensive analysis of the physical effects playing a role in the detection of gas molecules is carried out by TCAD simulations combined with interface characterization techniques. The complex interaction of charge transport in silicon nanowires of different dimensions with interface trap states and remote charges is addressed to correctly reproduce experimental results of recently fabricated gas nanosensors.

Design and optimization of components and processes for plasma sources in advanced material treatments

The research activities described in the present thesis have been oriented to the design and development of components and technological processes aimed at optimizing the performance of plasma sources in advanced in material treatments. Consumables components for high definition plasma arc cutting (PAC) torches were studied and developed. Experimental activities have in particular focussed on the modifications of the emissive insert with respect to the standard electrode configuration, which comprises a press fit hafnium insert in a copper body holder, to improve its durability. Based on a deep analysis of both the scientific and patent literature, different solutions were proposed and tested. First, the behaviour of Hf cathodes when operating at high current levels (250A) in oxidizing atmosphere has been experimentally investigated optimizing, with respect to expected service life, the initial shape of the electrode emissive surface. Moreover, the microstructural modifications of the Hf insert in PAC electrodes were experimentally investigated during first cycles, in order to understand those phenomena occurring on and under the Hf emissive surface and involved in the electrode erosion process. Thereafter, the research activity focussed on producing, characterizing and testing prototypes of composite inserts, combining powders of a high thermal conductibility (Cu, Ag) and high thermionic emissivity (Hf, Zr) materials The complexity of the thermal plasma torch environment required and integrated approach also involving physical modelling. Accordingly, a detailed line-by-line method was developed to compute the net emission coefficient of Ar plasmas at temperatures ranging from 3000 K to 25000 K and pressure ranging from 50 kPa to 200 kPa, for optically thin and partially autoabsorbed plasmas. Finally, prototypal electrodes were studied and realized for a newly developed plasma source, based on the plasma needle concept and devoted to the generation of atmospheric pressure non-thermal plasmas for biomedical applications.

Characterization and optimization of an x-ray laser for the spectroscopy of Li-like heavy-ions

Recent developments in the theory of plasma-based collisionally excited x-ray lasers (XRL) have shown an optimization potential based on the dependence of the absorption region of the pumping laser on its angle of incidence on the plasma. For the experimental proof of this idea, a number of diagnostic schemes were developed, tested, qualified and applied. A high-resolution imaging system, yielding the keV emission profile perpendicular to the target surface, provided positions of the hottest plasma regions, interesting for the benchmarking of plasma simulation codes. The implementation of a highly efficient spectrometer for the plasma emission made it possible to gain information about the abundance of the ionization states necessary for the laser action in the plasma. The intensity distribution and deflection angle of the pump laser beam could be imaged for single XRL shots, giving access to its refraction process within the plasma. During a European collaboration campaign at the Lund Laser Center, Sweden, the optimization of the pumping laser incidence angle resulted in a reduction of the required pumping energy for a Ni-like Mo XRL, which enabled the operation at a repetition rate of 10 Hz. Using the experiences gained there, the XRL performance at the PHELIX facility, GSI Darmstadt with respect to achievable repetition rate and at wavelengths below 20 nm was significantly improved, and also important information for the development towards multi-100 eV plasma XRLs was acquired. Due to the setup improvements achieved during the work for this thesis, the PHELIX XRL system now has reached a degree of reproducibility and versatility which is sufficient for demanding applications like the XRL spectroscopy of heavy ions. In addition, a European research campaign, aiming towards plasma XRLs approaching the water-window (wavelengths below 5 nm) was initiated.