Trading contracts with future commitments requires posting a collateral, called initial margin requirement, to cover associated risks. Differences in estimating those risks and varying risk appetites can however lead to identical contracts having different initial margin requirements at different market places. This creates a potential for minimizing those requirements by reallocating contracts. The task of minimizing the requirement is identified as a black-box optimization problem with constraints. The aim of this project was to investigate that optimization problem, how it can best be tackled, and comparing different techniques for doing so. Based on the results and obstacles encountered along the way, some guidelines are then outlined to provide assistance for whomever is interested in solving this or similar problems. The project consisted both of a literature study to examine existing knowledge within the subject of optimization, and an implementation phase to empirically test how well that knowledge can be put to use in this case. During the latter various algorithms were tested in a number of different scenarios. Focus was put on practical aspects that could be important in a real situation, such as how much they could decrease the initial margin requirement, execution time, and ease of implementation. As part of the literature study, three algorithms were found which were evaluated further: simulated annealing, differential evolution, and particle swarm optimization. They all work without prior knowledge of the function to be optimized, and are thus suitable for black-box optimization. Results from the implementation part showed largely similar performance between all three algorithms, indicating that other aspects such as ease of implementation or parallelization potential can be more important to consider when choosing which one to use. They were all well able to optimize different portfolios in a number of different cases. However, in more complex situations they required much more time to do so, showing a potential need to speed up the process.

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Yes / A compact planar monopole antenna is proposed for ultra-wideband applications. The antenna has a microstrip line feed and band-rejected characteristics and consists of a ring patch and partial ground plane with a defective ground structure of rectangular shape. An annular strip is etched above the radiating element and two slots, one C-shaped and one arc-shaped, are embedded in the radiating patch. The proposed antenna has been optimized using bio-inspired algorithms, namely Particle Swarm Optimization and the Firefly Algorithm, based on a new software algorithm (Antenna Optimizer). Multi-objective optimization achieves rejection bands at 3.3 to 3.7 GHz for WiMAX, 5.15 to 5.825 GHz for the 802.11a WLAN system or HIPERLAN/2, and 7.25 to 7.745 GHz for C-band satellite communication systems. Validated results show wideband performance from 2.7 to 10.6 GHz with S11 ˂ -10 dB. The antenna has compact dimensions of 28 × 30 mm2. The radiation pattern is comparatively stable across the operating band with a relatively stable gain except in the notched bands. / This work was supported in part by the United Kingdom Engineering and Physical Science Research Council (EPSRC) under Grant EP/E022936A, TSB UK under grant application KTP008734 and the Iraqi Ministry of Higher Education and Scientific Research.

This dissertation investigates the advantages of using curvilinear spars and ribs, termed SpaRibs, to design supersonic aircraft wing-box in comparison to the use of classic design concepts that employ straight spars and ribs. The intent is to achieve a more efficient load-bearing mechanism and to passively control aeorelastic behavior of the structure under the flight loads. The use of SpaRibs broadens the design space and allows for the natural frequencies and natural mode shape tailoring. The SpaRibs concept is implemented in a new MATLAB-based optimization framework referred to as EBF3SSWingOpt. This framework interfaces different analysis software to perform the tasks required. VisualDOC is used as optimizer; the generation of the SpaRibs geometry and of the structure Finite Element Model (FEM) is performed by MD.PATRAN; MD.NASTRAN is utilized to compute the weight of the structure, the linear static stress analysis and the linear buckling analysis required for the calculation of the response functions. EBF3SSWingOpt optimization scheme performs both the sizing and the shaping of the internal structural elements. Two methods are compared while optimizing the wing-box; a One-Step method in which sizing and topology optimization are carried out simultaneously and a Two-Step method, in which the sizing and topology optimization are carried out separately but in an iterative way. The optimization problem statements for the One-Step and the Two-Step methodologies are presented. Three methods to define the shape of the SpaRibs parametrically are described: (1) the Bounding Box and Base Curves method defines the shape of the SpaRibs based on the shape of two curves called Base Curves which are positioned into the Bounding Box, a rectangular region defined on the plane z=0 and containing the projection of the wing plan-form onto the same plane; (2) the Linked Shape method defines the shape of a set of SpaRibs in a one by one square domain of the natural space. The set of curves is subsequently transformed in the physical space for creating the wing structure geometry layout. The shape of each curve of each set is unique however, mathematical relations link their curvature in an effort to reduce the number of design variables; and (3) the Independent Shape parameterization is similar to the Linked Shape parameterization however, the shape of each curve is unique. The framework and parameterization methods described are applied to optimize different types of wing structures. Following results are presented and discussed: (1) a rectangular wing-box subjected to a chord-wise linearly varying load, optimized using SpaRibs parameterized with Bounding-Box and Base Curves method; (2) a rectangular wing-box subjected to a chord-wise linearly varying load, optimized using SpaRibs parameterized with Linked Shape method; (3) a generic fighter wing subjected to uniform distributed pressure load, optimized using SpaRibs parameterized with Bounding-Box and Base Curves method; (4) a general business jet wing subjected to pull-up maneuver loads computed using ZESt (ZONA Technology Inc. Steady Euler equations solver), optimized using SpaRibs parameterized with Independent Shape method; (5) a preliminary application of the Linked Shape parameterization to place SpaRibs into a high speed commercial transport aircraft wing-box characterized by high geometry layout complexity; and (6) an optimization of panels subjected to axial and shear loads using curvilinear stiffeners and grids of curvilinear stiffeners. The results for the optimization of the rectangular wing-box show 36.8% weight reduction from the baseline, when the Bounding Box and Base Curves parameterization is applied and the Two-Step framework is implemented. For the same structure the weight reduction amounts to 46.7% when the Linked Shape parameterization and the Two-Step framework are used. Similar results are obtained for the generic fighter wing-box structure. In this case, the weight saving is about 20%. Bounding Box and Base Curves parameterization and Two-Step framework are used. Finally, the weight reduction for the general business jet wing-box structure amounts to 17% of the baseline weight. In this case, the computation is carried out using the Independent Shape parameterization and the Two-Step framework. In general, the Two-Step optimization framework finds better optimal structure configurations as compared to the One-Step optimization framework. However, the computational time required to find to optimum with the Two-Step optimization is larger when a small number of particles are used in the particle swarm optimization method. For larger number of particles, the computational time for the two methods is comparable. Finally for very large number of particles the Two-Step optimization requires less computational time. It is also important to notice how the Two-Step framework consistently leads to a better optimum than the One-Step framework, for the same number of particles. / Ph. D.

Yes / An efficient multi-object evolutionary algorithms are proposed for optimizing frequency characteristics of antennas based on an interfacing created by Matlab environment. This interface makes a link with CST Microwave studio where the electromagnetic investigation of antenna is realized. Very small, compact printed monopole antenna is optimized for ultra- wideband (UWB) applications. Two objective functions are introduced; the first function intends to increase the impedance bandwidth, and second function to tune the antenna to resonate at a particular frequency. The two functions operate in the range of 3.2 to 10.6 GHz and depend on the level of return loss. The computed results provide a set of proper design for UWB system in which the bandwidth achieved is 7.5GHz at the resonance frequency 4.48GHz, including relatively stable gain and radiation patterns across the operating band.

Over the last two decades, chip design has been conducted at the register transfer (RT) Level using Hardware Descriptive Languages (HDL), such as VHDL and Verilog. The modeling at the behavioral level not only allows for better representation and understanding of the design, but also allows for encapsulation of the sub-modules as well, thus increasing productivity. Despite these benefits, validating a RTL design is not necessarily easier. Today, design validation is considered one of the most time and resource consuming aspects of hardware design. The high costs associated with late detection of bugs can be enormous. Together with stringent time to market factors, the need to guarantee the correct functionality of the design is more critical than ever. The work done in this thesis tackles the problem of RTL design validation and presents new frameworks for functional test generation. We use branch coverage as our metric to evaluate the quality of the generated test stimuli. The initial effort for test generation utilized simulation based techniques because of their scalability with design size and ease of use. However, simulation based methods work on input spaces rather than the DUT's state space and often fail to traverse very narrow search paths in large input spaces. To encounter this problem and enhance the ability of test generation framework, in the following work in this thesis, certain design semantics are statically extracted and recurrence relationships between different variables are mined. Information such as relations among variables and loops can be extremely valuable from test generation point of view. The simulation based method is hybridized with Z3 based symbolic backward execution engine with feedback among different stages. The hybridized method performs loop abstraction and is able to traverse narrow design paths without performing costly circuit analysis or explicit loop unrolling. Also structural and functional unreachable branches are identified during the process of test generation. Experimental results show that the proposed techniques are able to achieve high branch coverage on several ITC'99 benchmark circuits and their modified variants, with significant speed up and reduction in the sequence length. / Master of Science