Optical filters encompass a vast array of devices and structures for a wide variety of applications. Generally speaking, an optical filter is some structure that applies a designed amplitude and phase transform to an incident signal. Different classes of filters have vastly divergent characteristics, and one of the challenges in the optical design process is identifying the ideal filter for a given application and optimizing it to obtain a specific response. In particular, it is highly advantageous to obtain a filter that can be seamlessly integrated into an overall device package without requiring exotic fabrication steps, extremely sensitive alignments, or complicated conversions between optical and electrical signals. This dissertation explores three classes of nano-scale optical filters in an effort to obtain different types of dispersive response functions. First, dispersive waveguides are designed using a sub-wavelength periodic structure to transmit a single TE propagating mode with very high second order dispersion. Next, an innovative approach for decoupling waveguide trajectories from Bragg gratings is outlined and used to obtain a uniform second-order dispersion response while minimizing fabrication limitations. Finally, high Q-factor microcavities are coupled into axisymmetric pillar structures that offer extremely high group delay over very narrow transmission bandwidths. While these three novel filters are quite diverse in their operation and target applications, they offer extremely compact structures given the magnitude of the dispersion or group delay they introduce to an incident signal. They are also designed and structured as to be formed on an optical wafer scale using standard integrated circuit fabrication techniques. A number of frequency-domain numerical simulation methods are developed to fully characterize and model each of the different filters. The complete filter response, which includes the dispersion and delay characteristics and optical coupling, is used to evaluate each filter design concept. However, due to the complex nature of the structure geometries and electromagnetic interactions, an iterative optimization approach is required to improve the structure designs and obtain a suitable response. To this end, a Particle Swarm Optimization algorithm is developed and applied to the simulated filter responses to generate optimal filter designs.

In today's world, supply chains are facing market dynamics dominated by strong global competition, high labor costs, shorter product life cycles, and environmental regulations. Supply chains have evolved to keep pace with the rapid growth in these business dynamics, becoming longer and more complex. As a result, supply chains are systems with a great number of network connections among their multiple components. The interactions of the network components with respect to each other and the environment cause these systems to behave in a highly nonlinear dynamic manner. Ripple effects that have a huge, negative impact on the behavior of the supply chain (SC) are called instabilities. They can produce oscillations in demand forecasts, inventory levels, and employment rates and, cause unpredictability in revenues and profits. Instabilities amplify risk, raise the cost of capital, and lower profits. To reduce these negative impacts, modern enterprise managers must be able to change policies and plans quickly when those consequences can be detrimental. This research proposes the development of a methodology that, based on the concepts of asymptotic stability and accumulated deviations from equilibrium (ADE) convergence, can be used to stabilize a great variety of supply chains at the aggregate levels of decision making that correspond to strategic and tactical decision levels. The general applicability and simplicity of this method make it an effective tool for practitioners specializing in the stability analysis of systems with complex dynamics, especially those with oscillatory behavior. This methodology captures the dynamics of the supply chain by using system dynamics (SD) modeling. SD was the chosen technique because it can capture the complex relationships, feedback processes, and multiple time delays that are typical of systems in which oscillations are present. If the behavior of the supply chain shows instability patterns, such as ripple effects, the methodology solves an optimization problem to find a stabilization policy to remove instability or minimize its impact. The policy optimization problem relies upon a theorem which states that ADE convergence of a particular state variable of the system, such as inventory, implies asymptotic stability for that variable. The stabilization based on the ADE requires neither linearization of the system nor direct knowledge of the internal structure of the model. Moreover, the ADE concept can be incorporated easily in any SD modeling language. The optimization algorithm combines the advantage of particle swarm optimization (PSO) to determine good regions of the search space with the advantage of local optimization to quickly find the optimal point within those regions. The local search uses a Powell hill-climbing (PHC) algorithm as an improved procedure to the solution obtained from the PSO algorithm, which assures a fast convergence of the ADE. The experiments showed that solutions generated by this hybrid optimization algorithm were robust. A framework built on the premises of this methodology can contribute to the analysis of planning strategies to design robust supply chains. These improved supply chains can then effectively cope with significant changes and disturbances, providing companies with the corresponding cost savings.

Yes / To solve the multi-objective mobile robot path planning in a dangerous environment with dynamic obstacles, this paper proposes a modified membraneinspired algorithm based on particle swarm optimization (mMPSO), which combines membrane systems with particle swarm optimization. In mMPSO, a dynamic double one-level membrane structure is introduced to arrange the particles with various dimensions and perform the communications between particles in different membranes; a point repair algorithm is presented to change an infeasible path into a feasible path; a smoothness algorithm is proposed to remove the redundant information of a feasible path; inspired by the idea of tightening the fishing line, a moving direction adjustment for each node of a path is introduced to enhance the algorithm performance. Extensive experiments conducted in different environments with three kinds of grid models and five kinds of obstacles show the effectiveness and practicality of mMPSO. / National Natural Science Foundation of China (61170016, 61373047), the Program for New Century Excellent Talents in University (NCET-11-0715) and SWJTU supported project (SWJTU12CX008); grant of the Romanian National Authority for Scientific Research, CNCSUEFISCDI, project number PN-II-ID-PCE- 2011-3-0688.

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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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.