Boundary variation method and material distribution method are distinct approaches for structural optimization. In the early days, due to the fact that boundary variation methods were generally not able to handle topological changes, it was applied only in shape optimization problems where the topology of initial design is fixed during optimization process. To enable topological changes that are essential to deliver major performance improvements, material distribution method was introduced in the work of Bendsoe and Kikuchi, and thereafter widely adopted in nearly all aspects of topology optimization. Recently a novel boundary variation method for topology optimization was developed based on level set method, in which topological changes is allowed for. In the thesis, we study the level set based boundary variation method and material distribution method for structure optimization problem. / Finally, we studied the semi-Lagrange scheme to solve the Hamilton-Jacobi equation in level set based boundary variation method. In level set method, the free boundary of a structure is optimized via solution of a Hamilton-Jacobi equation. The numerical stability condition in explicit schemes for discrete Hamilton-Jacobi equation severely restricts the time step. To improve the numerical efficiency, we employ a semi-Lagrange scheme to solve Hamilton-Jacobi equation. Therefore, much larger time steps can be obtained and the number of iterations before convergence is greatly reduced. / Firstly, we studied the minimum compliance optimization problem of thermoelastic structures. In this optimization problem, we find that the optimal structures given by the state-of-art material distribution method, SIMP i method, generally have large area of intermediate density values that are not feasible in practical engineering applications because of their poor manufacturability and high costs. Therefore, we apply level set based boundary variation method in the optimization problem. As numerical results show, the optimal structures obtained are well suited to engineering applications. / To sum up, we explore in this thesis the boundary variation method and material distribution method for structure optimization problem. Several meaningful results and conclusions are obtained. / We secondly studied the stress minimization problem. In practical applications the most important requirement on a structure is often the strength of structure which characterizes the resistance to failure. In stress minimization problem, the objective is to minimize the distribution of von Mises stress in a structure. Here, level set method gives a significant convenience for stress optimization, in particular, we need not to incorporate any stress amplification factor of material microstructure which would be an important issue in material distribution method. Moreover, in order to derive more control of maximum stress, we utilize the Kreisselmeier-Steinhauser function to aggregate stresses at each point in a structure into a single global function. / Xia, Qi. / "October 2007." / Adviser: Michael Yu Wang. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 4993. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 102-111). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

The strategic importance of FMCG SME's supply chains makes it paramount that their performances are measured. Performance measurement in the context of on-time delivery is of high importance to SME's. SME's compete with large companies within the FMCG sector, as such gaining a competitive advantage is an extremely difficult task for these small and medium companies. There is an everincreasing interest toward the field of supply chain management and much attention has been deemed towards the importance of information sharing in gaining competitive advantage for SMEs. The integration of the chain both internally and externally through information sharing ( visibility) can lead to increase supply chain performance such as on-time delivery, therefore increasing competitive advantage for the SME's. The study aim to develop a conceptual framework and a model to evaluate the impact of visibility tools usage in FMCG SME's. This research highlights some visibility tools such as ERP systems, Sage software that influences the level of information shared among the parties within the SME supply chain. This research examined the potential of information technology based tools and visibility factors and aims to provide factors that may influence the sharing of information between suppliers and customers along the supply chain, thus meeting on time delivery schedules. This research employed both quantitative and qualitative approaches, with regression and correlation tests also conducted. Two questionnaires were administered, one at the case study company, the other at 100 SME's across London, 63 valid questionnaires were received and analyzed using SPSS software (manufactured by IBM, version 20). The findings of this research revealed that having shared values among SME's influenced the level of information that is shared and thus the level of visibility achieved within the supply chain. Further, it was revealed that large companies are able to utilize more in depth IT based systems, while small and medium sized companies had a tendency to utilize informal means for their visibility tools. In addition, the analysis of the research model indicated that supplier lead time and supplier chain reliability greatly influenced the ICT infrastructure of a FMCG SME. The model analysis also indicated that the delivery lead time influenced on-time delivery. In addition supply chain responsiveness was found to explain 30.9% of the variances found in supply chain visibility.

Thesis (Ph. D)--Massachusetts Institute of Technology, Dept. of Economics, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY. / Vita. / Bibliography: leaves 145-148. / Ph.D

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 67-72). / In this thesis, we designed and implemented a crowdsourcing system to annotate mouse behaviors in videos; this involves the development of a novel clip-based video labeling tools, that is more efficient than traditional labeling tools in crowdsourcing platform, as well as the design of probabilistic inference algorithms that predict the true labels and the workers' expertise from multiple workers' responses. Our algorithms are shown to perform better than majority vote heuristic. We also carried out extensive experiments to determine the effectiveness of our labeling tool, inference algorithms and the overall system. / by Yuzhao Ni. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2007. / Includes bibliographical references (p. 59-63). / We address the problem of designing a transportation network in the presence of demand uncertainty, multiple origin-destination pairs and a budget constraint for the overall construction cost, under the behavioral assumption that travelers optimize their own travel costs (i.e., the "user-equilibrium" condition). Under deterministic demand, we propose an exact integer optimization approach that leads to a quadratic objective, linear constraints optimization problem. As a result, the problem is efficiently solvable via commercial software, when the costs are linear functions of traffic flows. We then use an iterative algorithm to address the case of nonlinear cost functions. While the problem is intractable under probabilistic assumptions on demand uncertainty, we extend the previous model and propose an iterative algorithm using a robust optimization approach that models demand uncertainty. We finally report extensive numerical results to illustrate that our approach leads to tractable solutions for large scale networks. / by Yun Lu. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2006. / Includes bibliographical references (p. 55). / The symmetry function of a convex set offers us numerous useful information about the set in relation to probabilistic theory and geometric properties. The symmetry function is a measure of how symmetric the convex set is, and for a point, intuitively it measures how symmetric the set is with respect to that point. We call a point of high symmetry value a deep point. A random walk is a procedure that starts from a particular point in Rn and at each iteration, moves to a "neighboring" point according to some probability distribution that depends solely on the current point. The Hit-and-Run random walk on a convex set S picks a random line e through the point, and at next iteration goes to a new point that is chosen uniformly on the chord ℓ [intersection] S. In this thesis, we analyze and investigate the effectiveness of the Hit-and-Run random walk to compute a deep point in a convex body, given a randomly generated convex set. The effectiveness is evaluated in terms of the role of the starting point and the likelihood that the random walk will enter the zone of high symmetry. Additionally, some known probabilistic properties of the symmetry function are tested using the random walk, from which the integrity of the code is also verified. / (cont.) The final portion of this thesis analyzes the behavioral properties of convex sets that have non-Euclidean rounding, which renders the random walk less efficient. Therefore the pre-conditioned Hit-and-Run random walk is performed, and the performance is quantitatively presented in a power law equation that predicts the preconditioning iterations required, given the dimension of the convex set, a starting point near a corner and the width of that corner. / by Jiajie Liang. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2008. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Includes bibliographical references (p. 41-45). / Although perfectly matched layers (PMLs) have been widely used to truncate numerical simulations of electromagnetism and other wave equations, we point out important cases in which a PML fails to be reflectionless even in the limit of infinite resolution. In particular, the underlying coordinate-stretching idea behind PML breaks down in photonic crystals and in other structures where the material is not an analytic function in the direction perpendicular to the boundary, leading to substantial reflections. The alternative is an adiabatic absorber, in which reflections are made negligible by gradually increasing the material absorption at the boundaries, similar to a common strategy to combat discretization reflections in PMLs. We demonstrate the fundamental connection between such reflections and the smoothness of the absorption profile via coupled-mode theory, and show how to obtain higher-order and even exponential vanishing of the reflection with absorber thickness. / by Ardavan F. Oskooi. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 75-79). / Over 10,000 premature mortalities per year globally are attributed to the exposure to particulate matter caused by aircraft emissions. Unlike previous studies that focus on the regional impacts from the aircraft emissions below 3,000 feet, this thesis studies the impact from emissions at all altitudes and across continents on increasing particulates in a receptor region, thereby increasing exposure. In addition to these intercontinental impacts, the thesis analyzes the temporal variations of sensitivities of the air quality and health, the proportion of the impacts attributable to different emission species, and the background emissions' influence on the impact of aircraft emissions. To quantify the impacts of aircraft emissions at various locations and times, this study uses the adjoint model of GEOS-Chem, a chemical transport model. The adjoint method efficiently computes sensitivities of a few objective functions, such as aggregated PM concentration and human exposure to PM concentration, with respect to many input parameters, i.e. emissions at different locations and times. Whereas emissions below 3,000 feet have mostly local impacts, cruise emissions from North America impair the air quality in Europe and Asia, and European cruise emissions affect Asia. Due to emissions entering Asia, the premature mortalities in Asia were approximately two to three times larger than the global mortalities caused by the Asian emissions. In contrast, North America observed only about one-ninth of the global premature mortalities caused by North American emissions because emissions get carried out of the region. This thesis calculates that most of the premature mortalities occured in Europe and Asia in 2006. Sensitivities to emissions also have seasonal and diurnal cycles. For example, ground level NOx emissions in the evening contribute to 50% more surface PM formation than the same emissions in the morning, and cruise level NOx emissions in early winter cause six times more PM concentration increase than the same emissions in spring. Aircraft NOx emissions cause 78% of PM from aviation emissions, and given the population exposure to PM concentration increase, NOx contributes 90% of the total impact. By showing the second-order sensitivities, this study finds that increases in background emissions of ammonia increase the impact of aircraft emissions on the air quality and increases in background NOx emissions decrease the impact. These results show the effectiveness of the adjoint model for analyzing the longterm sensitivities. Some of the analyses presented are practically only possible with the adjoint method. By regulating emissions at high sensitivities in time and region, calculated by the adjoint model, governments can design effective pollutant reduction policies. / by Jamin Koo. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 73-76). / This thesis consists of a simulation-based study and a data visualization framework development focusing on malaria transmission in West Africa. The simulation-based study introduces the concept of hysteresis in malaria transmission, which is defined as the dependence of malaria transmission on initial conditions of the system, characterizing the dry season. The simulation results confirm that the hysteresis effect does exist in malaria transmission demonstrated in the significant effects of initial prevalence and immunity level of the population. The persistence of the hysteresis effect is stronger in a relatively high transmission environment than in low transmission environments. In addition, the study highlights the importance of sustainable malaria control and resource allocation in the reduction of malaria transmission. It illustrates that exposure-reduction malaria control programs like the distribution of insecticide-treated nets (ITNs) will result in a loss of acquired immunity for the population. If the ITN coverage is discontinued after a period of time, relatively strong malaria resurgence will occur. This thesis also presents a web-based mapping and visualization tool for spatio-temporal data like malaria transmission predictions. The framework is developed using open source software and is not only interactive but also web-based; hence, it can deliver spatio-temporal data to the public more effectively than traditional applications. The tool contains the following two main components: the visualization interface and the interactive maps. When the user interacts with the tool, such as clicking on the map, relevant graphics and numerical data will be requested and displayed in the visualization interface. The interactive map, facilitated by animation controls, allows users to view map animations and explore how different climate and malaria transmission data changes over time and space. The visualization framework itself is customizable and has also been used to publish and visualize temperature projections in Southwest Asia. / by Xin Qiu. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2014. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 89-94). / The ability to achieve accurate predictions of turbulent flow over arbitrarily complex geometries proves critical in the advancement of aerospace design. However, quantitatively accurate results from modern Computational Fluid Dynamics (CFD) tools are often accompanied by intractably high computational expenses and are significantly hindered by the lack of automation. In particular, the generation of a suitable mesh for a given flow problem often requires significant amounts of human input. This process however encounters difficulties for turbulent flows which exhibit a wide range of length scales that must be spatially resolved for an accurate solution. Higher-order adaptive methods are attractive candidates for addressing these deficiencies by promising accurate solutions at a reduced cost in a highly automated fashion. However, these methods in general are still not robust enough for industrial applications and significant advances must be made before the true realization of robust automated three-dimensional turbulent CFD. This thesis presents steps towards this realization of a robust high-order adaptive Reynolds-Averaged Navier-Stokes (RANS) method for the analysis of turbulent flows. Specifically, a discontinuous Galerkin (DG) discretization of the RANS equations and an output-based error estimation with an associated mesh adaptation algorithm is demonstrated. To improve the robustness associated with the RANS discretization, modifications to the negative continuation of the Spalart-Allmaras turbulence model are reviewed and numerically demonstrated on a test case. An existing metric-based adaptation framework is adopted and modified to improve the procedure's global convergence behavior. The resulting discretization and modified adaptation procedure is then applied to two-dimensional and three-dimensional turbulent flows to demonstrate the overall capability of the method. / by Jun Kudo. / S.M.