Current aircraft conceptual design practices result in the selection of a single (hopefully) Pareto optimal design to be carried forward into preliminary design. This paradigm is based on the assumption that carrying a significant number of concepts forward is too costly and thus early down-selection between competing concepts is necessary. However, this approach requires that key architectural design decisions which drive performance and market success are fixed very early in the design process, sometimes years before the aircraft actually goes to market. In the presence of uncertainty, if the design performance is examined for individual scenarios as opposed to measuring performance of the design with aggregate statistics, the author finds that the single concept approach can lead to less than desirable design outcomes. This thesis proposes an alternate conceptual design paradigm which leverages principles from economics (specifically the Nobel prize-winning modern portfolio theory) to improve design outcomes by intelligently selecting a small well diversified portfolio of concepts to carry forward through preliminary design, thus reducing the risk from external events that are outside of the engineer’s control. This alternate paradigm is expected to result in an increase in the overall profit by increasing the probability that the final design matches market needs at the time it goes to market. This thesis presents a portfolio based design approach, which leverages dynamic programming to enable a stochastic optimization of alternative portfolios of concepts. This optimization returns an optimized portfolio of concepts which are iteratively pruned to improve design outcomes in the presence of scenario-driven uncertainties. While dynamic programming is identified as a means for doing a stochastic portfolio optimization, dynamic programming is an analytical optimization process which suffers heavily from the curse of dimensionality. As a result, a new hybrid stochastic optimization process called the Evolutionary Cooperative Optimization with Simultaneous Independent Sub-optimization (ECOSIS) has been introduced. The ECOSIS algorithm leverages a co-evolutionary algorithm to optimize a multifaceted problem under uncertainty. ECOSIS allows for a stochastic portfolio optimization including the desired benefit-to-cost tradeoff for a well-diversified portfolio at the size and scope required for use in design problems. To demonstrate the applicability and value of a portfolio based design approach, an example application of the approach to the selection of a new 300 passenger aircraft is presented.

Submitted by Alison Vanceto (alison-vanceto@hotmail.com) on 2017-02-14T11:18:13Z No. of bitstreams: 1 TeseAHMP.pdf: 2470407 bytes, checksum: b3f2c2d64bfa00285c28963c74627bea (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-03-20T13:12:18Z (GMT) No. of bitstreams: 1 TeseAHMP.pdf: 2470407 bytes, checksum: b3f2c2d64bfa00285c28963c74627bea (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-03-20T13:12:31Z (GMT) No. of bitstreams: 1 TeseAHMP.pdf: 2470407 bytes, checksum: b3f2c2d64bfa00285c28963c74627bea (MD5) / Made available in DSpace on 2017-03-20T13:23:55Z (GMT). No. of bitstreams: 1 TeseAHMP.pdf: 2470407 bytes, checksum: b3f2c2d64bfa00285c28963c74627bea (MD5) Previous issue date: 2014-12-02 / Não recebi financiamento / The process of building the knowledge base of fuzzy systems has benefited extensively of methods to automatically extract the necessary knowledge from data sets that represent examples of the problem. Among the topics investigated in the most recent research is the matter of balance between accuracy and interpretability, which has been addressed by means of multi-objective genetiv algorithms, NSGA-II being on of the most popular. In this scope, we identified the need to control the diversity of solutions found by these algorithms, so that each solution would balance the Pareto frontier with respect to the goals optimized by the multi-objective genetic algorithm. In this PhD thesis a multi-objective genetic algorithm, named NSGA-DO, is proposed. It is able to find non dominated solutions that balance the Pareto frontier with respect optimization of the objectives. The main characteristicof NSGA-DO is the distance oriented selection of solutions. Once the Pareto frontier is found, the algorithm uses the locations of the solutions in the frontier to find the best distribution of solutions. As for the validation of the proposal, NSGA-DO was applied to a methodology for the generation of fuzzy knowledge bases. Experiments show the superiority of NSGADO when compared to NSGA-II in all three issues analyzed: dispersion, accuracy and interpretability. / A construção da base de conhecimento de sistemas fuzzy tem sido beneficiada intensamente por métodos automáticos que extraem o conhecimento necessário a partir de conjuntos de dados que representam exemplos do problema. Entre os tópicos mais investigados nas pesquisas recentes está a questão do balanceamento entre acuidade e interpretabilidade, que têm sido abordada por meio dos algoritmos genéticos multiobjetivo, sendo o NSGA-II um dos mais populares. Neste escopo, identificou-se a necessidade do controle da distribuição das soluções encontradas por estes algoritmos, a fim de que cada solução possa equilibrar a fronteira de Pareto com relação aos objetivos otimizados pelo algoritmo genético multiobjetivo. Neste sentido, desenvolveu-se neste projeto de doutorado um algoritmo genético multiobjetivo, chamado NSGA-DO, capaz de encontrar soluções não dominadas que equilibram a fronteira de Pareto nos objetivos a serem otimizados. A principal característica do NSGA-DO é a seleção de soluções orientada à distância. Uma vez encontrada a fronteira de Pareto, o algoritmo usa a localização das soluções nesta fronteira para encontrar a melhor distribuição das soluções. Para a validação da proposta, aplicou-se o NSGA-DO em uma metodologia para a geração de bases de conhecimento fuzzy. Experimentos realizados comprovaram a superioridade do NSGA-DO com relação ao NSGA-II nos três quesitos analisados: dispersão, acurácia e interpretabilidade.

Face aux exigences concurrentielles et économiques actuelles dans le secteur automobile, l'emboutissage a l'avantage, comme étant un procédé de mise en forme par grande déformation, de produire, en grandes cadences, des pièces de meilleure qualité géométrique par rapport aux autres procédés de fabrication mécanique. Cependant, il présente des difficultés de mise en œuvre, cette dernière s'effectue généralement dans les entreprises par la méthode classique d'essai-erreur, une méthode longue et très coûteuse. Dans la recherche, le recours à la simulation du procédé par la méthode des éléments finis est une alternative. Elle est actuellement une des innovations technologiques qui cherche à réduire le coût de production et de réalisation des outillages et facilite l'analyse et la résolution des problèmes liés au procédé. Dans le cadre de cette thèse, l'objectif est de prédire et de prévenir, particulièrement, le retour élastique et la rupture. Ces deux problèmes sont les plus répandus en emboutissage et présentent une difficulté en optimisation puisqu'ils sont antagonistes. Une pièce mise en forme par emboutissage à l'aide d'un poinçon sous forme de croix a fait l'objet de l'étude. Nous avons envisagé, d'abord, d'analyser la sensibilité des deux phénomènes concernés par rapport à deux paramètres caractéristiques du procédé d'emboutissage (l'épaisseur du flan initial et de la vitesse du poinçon), puis par rapport à quatre (l'épaisseur du flan initial, de la vitesse du poinçon, l'effort du serre flan et le coefficient du frottement) et finalement par rapport à la forme du contour du flan. Le recours à des méta-modèles pour optimiser les deux critères était nécessaire. / The processing of sheet metal forming is of vital importance to a large range of industries as production of car bodies, cans, appliances, etc. It generates complex and precise parts. Although, it is an involved technology combining elastic-plastic bending and stretch deformation of the workpiece. These deformations can lead to undesirable problems in the desired shape and performance of the stamped. To perform a successful stamping process and avoid shape deviations such as springback and failure defects, process variables should be optimized.In the present work, the objective is the prediction and the prevention of, especially, springback and failure. These two phenomena are the most common problems in stamping process that present much difficulties in optimization since they are two conflicting objectives. The forming test studied in this thesis concern the stamping of an industrial workpiece stamped with a cross punch. To solve this optimization problem, the approach chosen was based on the hybridization of an heuristic and a direct descent method. This hybridization is designed to take advantage from both disciplines, stochastic and deterministic, in order to improve the robustness and the efficiency of the hybrid algorithm. For the multi-objective problem, we adopt methods based on the identification of Pareto front. To have a compromise between the convergence towards the front and the manner in which the solutions are distributed, we choose two appropriate methods. This methods have the capability to capture the Pareto front and have the advantage of generating a set of Pareto-optimal solutions uniformly spaced. The last property can be of important and practical.

This paper deals with multi-objective optimization problems (MOOP). It is explained, what solutions in multi-objetive search space are optimal and how are optimal (non-dominated) solutions found in the set of feasible solutions. Afterwards, principles of NSGA-II, MOPSO and GDE3 algorithms are described. In the following chapters, benchmark metrics and problems are introduced. In the last part of this paper, all the three algorithms are compared based on several benchmark metrics.

Getinge AB is a global medical technology company. This master’s thesis is based on the outflow of capital equipments from Getinge’s factory in Växjö to four different sales and service units. The purpose of this thesis is to give Getinge a deeper insight of why the customers and the own organization do not know when they can expect their products. This makes most requests urgent and thus prohibits them from using the best environmental and cost efficient modes of transportation. Two sub-problems have been created in order to investigate this. Sub-problem 1 originates from an organizational perspective. The aim of this problem is to examine the possibilities to achieve less urgent transportations by improving the communication between sales and service units, factories and logistics services. This is evaluated based on semi-structured interviews containing both qualitative and quantitative questions with employees rep- resenting the different functions at the company. It appeared that different phrases, explaining the same thing, were used internally leading to confu- sion. Further, the different functions have harmonized follow-up sessions but do not share the information between each other. The resulting information vacuum creates trust issues and unnecessary time margins and buffers. Sub-problem 2 concerns the trade-off between the economic and environmen- tal impacts in relation to the Greenhouse Gas Protocol Scope 3. This trade- off is evaluated by a multi-objective optimization model, where emissions are priced based on the EU ETS market valuation. Current research argues that the choice of transportation mode is the simplest emissions abatement option in terms of implementation. This study indicates that it is possible for Getinge, in the short-term, to decrease costs and emissions by just chang- ing between current transportation modes. However, a long-term strategy should include evaluation of consolidations, alternative fuels and electrified vehicles since the cost of decreasing one kilogram of emissions by changing between current transportation modes will increase. Finally, increased transparency and communication between sales and ser- vice units, factory and logistics services could be achieved via a one point of contact solution. This could avoid unnecessary time margins and buffers and hence open up the possibility of better over all lead time utilization. This could make it easier to use more environmental friendly transportation modes and thus lower emissions and costs, while still satisfying the customers.

The aim of this master thesis is to study algorithms for automatically tuning antenna parameters to improve the performance of the radio access part of a telecommunication network and user experience. There are four dierent optimization algorithms, Stepwise Minimization Algorithm, Random Search Algorithm, Modied Steepest Descent Algorithm and Multi-Objective Genetic Algorithm to be applied to a model of a radio access network. The performances of all algorithms will be evaluated in this thesis. Moreover, a graphical user interface which is developed to facilitate the antenna tuning simulations will also be presented in the appendix of the report.

面對通訊與資訊科技的大幅進步，通訊網路正在進行一個巨大的變革，要將電信網路與數據網路整合成一個單一的All-IP網路以支援所有網路應用服務。欲達到整合型網路的理想，仍有許多困難尚待克服，而服務品質問題是其中最關鍵的問題之一。因為受限於封包交換網路之原有的特性，All-IP網路有影響服務品質的三項因素：過長的延遲時間、抖動以及封包遺失。首先，我們利用了達成度函數(achievement function)來處理單位的轉換，使得能夠同時考量此三項不同單位的因素。接著，本文中提出一套方法來解決All-IP網路上端對端(end-to-end)的資源配置及路徑規劃問題。在分配資源時，我們企圖提供一種成比例的公平性給各個不同等級。此公平性的精神是要使得所有網路使用者的滿足程度相當，而非各個不同等級的使用者分配到相同的資源。我們將以預算方式控制端對端品質管理以追求使用者之整體最大滿意程度。 本論文的規劃概念是將網路規劃分成兩個階段。第一階段是在一筆給定的總預算底下，以成比例的方式去分配資源給各個不同等級，並建置網路上的頻寬，使各等級能依其需求拿到適當的頻寬，確保滿足程度相當。 接下來第二階段則是在第一部份已完成的規劃基礎下，做路徑規劃，指派新進入的使用者到一條較好的路徑，在滿足此使用者的延遲時間要求下，使此系統的壅塞程度越小越好。路徑規劃的概念為如何挑選最佳網路路徑，以規劃具服務品質之端對端路徑，並可達到資源之最有效利用。網路營運者將可運用此套方法來調校自身所營運的網路以追求使用者最高滿意度。 / We present an approach for the fair resource allocation problem and QoS routing in All-IP networks that offer multiple services to users. The objective of the optimization problem is to determine the amount of required bandwidth for each link and each class to maximize the sum of the users' utility. In this work, we focus on approaches that, while allocating bandwidth, attempt to provide a proportionally fair treatment of all the competing classes. First, we will show that an achievement function can map different criteria subject to various utility onto a normalized scale. It may be interpreted as a measure of QoS (Quality of Service) on All-IP networks. Using the bandwidth allocation model, we can find a Pareto optimal allocation of bandwidth on the network under a limited available budget. This allocation can provide the so-called proportional fairness to every class, that is, this allocation can provide the similar satisfaction to each user. Next, we present a routing scheme under consideration of the delay. Such an optimal path provides the end-to-end QoS guarantees to each user. Finally, a numerical example is given to illustrate how to solve the fair resource allocation problem and how to modify the nonlinear parts.

In a quest to design novel deployable structures, flexible polyhedra provide interesting insights. This work follows the discovery of flexible polyhedra and aims to make flexible polyhedra more useful. The dissertation describes how flexible polyhedra can be made. The flexible polyhedra first considered in this dissertation have a rotational degree of freedom. The range of this rotational movement is measured and maximised in this work by numerical maximisation. All polyhedra are established computationally: an iterative solution method is used to find vertex coordinates; several clash detecting methods are described to define whether each rotational position of a flexible polyhedron is physically possible; then a range of motion is defined between occurrences of clashes at the two ends; finally, an optimisation tool is used to maximise the range of motion. By using these tools, the range of motion of two types of simplest flexible polyhedra are maximised. The first type is a series of flexible polyhedra generalised from the Steffen flexible polyhedron. The range of motion of this type is improved to double that of Steffen’s original, from 27° to 59°. Another type of flexible polyhedron is expanded from a model provided by Tachi. Based on the understanding of Steffen’s flexible polyhedron, optimisation parameters are carefully given. This new type has achieved a wider range of motion, so now the range of motion of flexible polyhedron is tripled to 80°. After enlarging the range of motion of the degree of freedom in the 1-dof systems, the dissertation found multiple degrees of freedom in one polyhedron. The multiple mechanisms can be even repetitive, so that an n-dof polyhedron is found. A polyhedron of two degrees of freedom is first presented. Then, a unit cell for any number of mechanisms is found. As a repetitive structure, a 3-dof polyhedron is presented. Finally, this work presents the possibility of configuring a flexible polyhedral torus and a closed polyhedral surface that is able to flex without the need to stop.