Technology has a major role in today’s world. The development and massive access to information technology has enabled the use of computers to provide assistance on a wide range of tasks, from the most trivial daily ones to the most complex challenges we face as human kind. In particular, optimisation algorithms assist us in taking decisions, improving processes, designing solutions and they are successfully applied in several contexts such as industry, health, entertainment, and so on. The design and development of effective and efficient computational algorithms is, thus, a need in modern society.Developing effective and efficient optimisation algorithms is an arduous task that includes designing and testing of several algorithmic components and schemes, and requires considerable expertise. During the design of an algorithm, the developer defines parameters, that can be used to further adjust the algorithm behaviour depending on the particular application. Setting appropriate values for the parameters of an algorithm can greatly improve its performance. This way, most high-performing algorithms define parameter settings that are “finely tuned”, typically by experts, for a particular problem or execution condition.The process of finding high-performing parameter settings, called algorithm configuration, is commonly a challenging, tedious, time consuming and computationally expensive task that hinders the application and design of algorithms. Nevertheless, the algorithm configuration process can be modelled as an optimisation problem itself and optimisation techniques can be applied to provide high-performing configurations. The use of automated algorithm configuration procedures, called configurators, allows obtaining high-performing algorithms without requiring expert knowledge and it enables the design of more flexible algorithms by easing the definition of design choices as parameters to be set. Ultimately, automated algorithm configuration could be used to fully automatise the algorithm development process, providing algorithms tailored to the problem to be solved.The aim of the work presented in this thesis is to study the automated configuration of algorithms. To do so, we formally define the algorithm configuration problem and analyse its characteristics. We study the most prominent algorithm configuration procedures and identify relevant configuration techniques and their applicability. We contribute to the field by proposing and analysing several configuration procedures, being the most prominent of these the irace configurator. This work presents and studies several modifications of the configuration process implemented by irace, which considerably improve the performance of irace and broaden its applicability. In a general context, we provide insights about the characteristics of the algorithm configuration process and techniques by performing several analyses configuring different types of algorithms under varied situations. And, finally, we provide practical examples of the usage of automated configuration techniques showing its benefits and further uses for the application and design of efficient and effective algorithms. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, Scientific-quality models are expensive to obtain using conventional aircraft-based methods. Photogrammetry-based techniques have no direct measurements, and thus has uncertainty in the reconstruction. The concept of a texel camera, which has both aerial imagery and ladar measurements from an inexpensive small UAV, can be used to combine the two methods. A texel camera fuses calibrated ladar measurements and electro-optical imagery upon simultaneous capture, creating a texel image. This eliminates the problem of fusing the data in a post-processing step and enables both 2D- and 3D-image registration techniques to be used. A texel camera outputs texel swaths during a UAV flight. A swath consists of an aerial image that is calibrated to associated depth measurements. This thesis describes an automatic algorithm for registering these texel swaths into a TDEM. The algorithm involves image processing, 3D geometry, and nonlinear optimization processes. The algorithm is seeded with a coarse estimate of the position and attitude of each texel swath capture, obtained using an on-board navigation system. Analysis of several data sets registered using this algorithm is shown. This method enables an inexpensive alternative to obtaining high quality textured 3D landscapes.

Triangle meshes have become an increasingly popular shape representation. Given the ease of standardization it allows and the proliferation of devices (scanners, range images ) that capture and output shape information as meshes, this representation is now used in applications such as virtual reality, medical imaging, rapid prototyping, digital art and entertainment, simulation and analysis, product design and development. In product development manipulation of mesh models is required in applications such as visualization, analysis, simulation and rapid prototyping. The nature of manipulation of the mesh includes annotation, interactive viewing, slicing, re-meshing, mesh optimization, mesh segmentation, simplification and editing. Of these editing has received the least attention. Mesh model often requires editing either locally or globally based on the application. With the increased use of meshes it is desirable to have formal reasoning tools that enable manipulation of mesh models in product development. The mesh model may contain artifacts like self-intersection, overlapping triangles, inconsistent normal’s of triangles and gaps or holes with or without islands. It is necessary to repair the mesh before further processing the mesh model. An automatic algorithm is proposed to repair and fill arbitrary holes while maintaining curvature continuity across the boundaries of the hole. The algorithm uses slices across the hole to first identify curves that bridge the hole. These curves are then used to find the surface patch that would fill the hole. The proposed algorithm works for arbitrary holes in any mesh model irrespective of the type of underlying surface and is able to preserve features in the mesh model that are missing in the input information. Since editing during product development is mostly feature based, an automatic algorithm to recognize shape features by directly clustering the triangles constituting a feature in a mesh model is proposed. Shape features addressed in the thesis are volumetric features that are associated with either addition or removal of a finite volume. The algorithm involves two steps – isolating features in 2D slices followed by a 3D traversal to cluster all the triangles in the feature. Editing a mesh model mainly implies editing local volumetric features in that model. An automatic algorithm is proposed for parametric editing of volumetric features in the mesh model. The proposed algorithm eliminates the need of original CAD model while manipulating any volumetric feature in the mesh model based on feature parameters. An automatic algorithm to manipulate global shape parameters of the object using the mesh model is developed. Global shape parameters include thickness, drafts and axes of symmetry. As the mesh models do not explicitly carry this information global editing of mesh models (other than for visualization) has not been attempted thus far. This thesis proposes the use of mid-surface to identify and manipulate global shape parameters for a class of objects that are classified as thin walled objects. Mid-curves are first identified on slices of the part and then the mid-surface is obtained from these mid-curves. Results of implementation are presented and discussed along with the scope for future work.