Dissertations / Theses on the topic 'Joint optimization'
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Frick, Eric. "Joint center estimation by single-frame optimization." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6575.
Full textKhojastehnia, Mahdi. "Massive MIMO Channels Under the Joint Power Constraints." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39992.
Full textWiddowson, Brian L. "A joint service optimization of the phased threat distribution." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA344694.
Full textThesis advisor(s): Richard E. Rosenthal. "March 1998."-Cover. Includes bibliographical references (p. 69). Also available online.
Ramachandran, Iyappan. "Joint PHY-MAC optimization for energy-constrained wireless networks /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/5968.
Full textSherrod, Vallan Gray. "Design Optimization for a Compliant,Continuum-Joint, Quadruped Robot." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7766.
Full textSanthanam, Arvind V. "Joint optimization of radio resources in wireless multihop networks /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3158467.
Full textFurst, Séverine. "Multi-objective optimization for joint inversion of geodetic data." Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTS017/document.
Full textThe Earth’s surface is affected by numerous local processes like volcanic events, landslides or earthquakes. Along with these natural processes, anthropogenic activities including extraction and storage of deep resources (e.g. minerals, hydrocarbons) shape the Earth at different space and time scales. These mechanisms produce ground deformation that can be detected by various geodetic instruments like GNSS, InSAR, tiltmeters, for example. The purpose of the thesis is to develop a numerical tool to provide the joint inversion of multiple geodetic data associated to plate deformation or volume strain change at depth. Four kinds of applications are targeted: interseismic plate deformation, volcano deformation, deep mining, and oil & gas extraction. Different inverse model complexities were considered: the I-level considers a single type of geodetic data with a time independent process. An application is made with inverting GPS data across southern California to determine the lateral variations of lithospheric rigidity (Furst et al., 2017). The II-level also accounts for a single type of geodetic data but with a time-dependent process. The joint determination of strain change history and the drift parameters of a tiltmeter network is studied through a synthetic example (Furst et al., submitted). The III-level considers different types of geodetic data and a timedependent process. A fictitious network made by GNSS, InSAR, tiltmeters and levelling surveys is defined to compute the time dependent volume change of a deep source of strain. We develop a methodology to implement these different levels of complexity in a single software. Because the inverse problem is possibly ill-posed, the functional to minimize may display several minima. Therefore, a global optimization algorithm is used (Mohammadi and Saïac, 2003). The forward part of the problem is treated by using a collection of numerical and analytical elastic models allowing to model the deformation processes at depth. Thanks to these numerical developments, new advances for inverse geodetic problems should be possible like the joint inversion of various types of geodetic data acquired for volcano monitoring. In this perspective, the possibility to determine by inverse problem the tiltmeter drift parameters should allow for a precise determination of deep strain sources. Also, the developed methodology can be used for an accurate monitoring of oil & gas reservoir deformation
Giannakas, Theodoros. "Joint modeling and optimization of caching and recommendation systems." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS317.
Full textCaching content closer to the users has been proposed as a win-win scenario in order to offer better rates to the users while saving costs from the operators. Nonetheless, caching can be successful if the cached files manage to attract a lot of requests. To this end, we take advantage of the fact that the internet is becoming more entertainment oriented and propose to bind recommendation systems and caching in order to increase the hit rate. We model a user who requests multiple contents from a network which is equipped with a cache. We propose a modeling framework for such a user which is based on Markov chains and depart from the IRM. We delve into different versions of the problem and derive optimal and suboptimal solutions according to the case we examine. Finally we examine the variation of the Recommendation aware caching problem and propose practical algorithms that come with performance guarantees. For the former, the results indicate that there are high gains for the operators and that myopic schemes without a vision, are heavily suboptimal. While for the latter, we conclude that the caching decisions can significantly improve when taking into consideration the underlying recommendations
Diehl, Douglas D. "How to optimize joint theater ballistic missile defense." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Mar%5FDiehl.pdf.
Full textFoster, James C. "Joint optimization of the technical and social aspects of workplace design." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/31002.
Full textMICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY.
Bibliography: leaves 91-97.
by James C. Foster.
M.S.
Fallgren, Mikael. "Optimization of Joint Cell, Channel and Power Allocation in Wireless Communication Networks." Doctoral thesis, KTH, Optimeringslära och systemteori, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-40274.
Full textFinancial support by the Swedish Foundation for Strategic Research (SSF) QC 20110915
Rao, Tingting. "LP-based subgradient algorithm for joint pricing and inventory control problems." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45282.
Full textIncludes bibliographical references (p. 93-94).
It is important for companies to manage their revenues and -reduce their costs efficiently. These goals can be achieved through effective pricing and inventory control strategies. This thesis studies a joint multi-period pricing and inventory control problem for a make-to-stock manufacturing system. Multiple products are produced under shared production capacity over a finite time horizon. The demand for each product is a function of the prices and no back orders are allowed. Inventory and production costs are linear functions of the levels of inventory and production, respectively. In this thesis, we introduce an iterative gradient-based algorithm. A key idea is that given a demand realization, the cost minimization part of the problem becomes a linear transportation problem. Given this idea, if we knew the optimal demand, we could solve the production problem efficiently. At each iteration of the algorithm, given a demand vector we solve a linear transportation problem and use its dual variables in order to solve a quadratic optimization problem that optimizes the revenue part and generates a new pricing policy. We illustrate computationally that this algorithm obtains the optimal production and pricing policy over the finite time horizon efficiently. The computational experiments in this thesis use a wide range of simulated data. The results show that the algorithm we study in this thesis indeed computes the optimal solution for the joint pricing and inventory control problem and is efficient as compared to solving a reformulation of the problem directly using commercial software. The algorithm proposed in this thesis solves large scale problems and can handle a wide range of nonlinear demand functions.
by Tingting Rao.
S.M.
Yamani, Jana H. (Jana Hashim). "Approximation of the transient joint queue-length distribution in tandem networks." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85470.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 95-97).
This work considers an urban traffic network, and represents it as a Markovian queueing network. This work proposes an analytical approximation of the time-dependent joint queue-length distribution of the network. The challenge is to provide an accurate analytical description of between and within queue (i.e. link) dynamics, while deriving a tractable approach. In order to achieve this, we use an aggregate description of queue states (i.e. state space reduction). These are referred to as aggregate (queue-length) distributions. This reduces the dimensionality of the joint distribution. The proposed method is formulated over three different stages: we approximate the time-dependent aggregate distribution of 1) a single queue, 2) a tandem 3-queue network, 3) a tandem network of arbitrary size. The third stage decomposes the network into overlapping 3-queue sub-networks. The methods are validated versus simulation results. We then use the proposed tandem network model to solve an urban traffic signal control problem, and analyze the added value of accounting for time-dependent between queue dependency in traffic management problems for congested urban networks.
by Jana H. Yamani.
S.M.
Chen, Yuan. "Joint Design of Redundancy and Maintenance for Parallel-Series Continuous-State Systems." Ohio University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1628594957896883.
Full textChen, Yuan. "Joint Design of Redundancy and Maintenance for Parallel-Series Continuous-State Systems." Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1628594957896883.
Full textKeskin, Burcu Baris. "Joint optimization of location and inventory decisions for improving supply chain cost performance." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2528.
Full textLiu, Fenghua. "Joint optimization of source and channel coding based on a nonlinear estimate receiver." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq24328.pdf.
Full textNesbitt, Jesse. "Robust Optimization in Operational Risk: A Study of the Joint Platform Allocation Tool." Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43063.
Full textLee, Jinwoo. "Joint Optimization of Pavement Management and Reconstruction Policies for Segment and System Problems." Thesis, University of California, Berkeley, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3733346.
Full textThis dissertation presents a methodology for the joint optimization of a variety of pavement construction and management activities for segment and system problems under multiple budget constraints. The objective of pavement management is to minimize the total discounted life time costs for the agency and the highway users by finding optimal policies. The scope of the dissertation is focused on continuous time and continuous state formulations of pavement condition. We use a history-dependent pavement deterioration model to account for the influence of history on the deterioration rate.
Three topics, representing different aspects of the problem are covered in the dissertation. In the first part, the subject is the joint optimization of pavement design, maintenance and rehabilitation (M&R;) strategies for the segment-level problem. A combination of analytical and numerical tools is proposed to solve the problem. In the second part of the dissertation, we present a methodology for the joint optimization of pavement maintenance, rehabilitation and reconstruction (MR&R;) activities for the segment-level problem. The majority of existing Pavement Management Systems (PMS) do not optimize reconstruction jointly with maintenance and rehabilitation policies. We show that not accounting for reconstruction in maintenance and rehabilitation planning results in suboptimal policies for pavements undergoing cumulative damage in the underlying layers (base, sub-base or subgrade). We propose dynamic programming solutions using an augmented state which includes current surface condition and age. In the third part, we propose a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. Within a bottom-up solution approach, Genetic Algorithm (GA) is adopted. The complexity of the algorithm is polynomial in the size of the system and the policy-related parameters.
Alam, Md Zahangir. "Joint transceiver design and power optimization for wireless sensor networks in underground mines." Master's thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/30663.
Full textWith the great developments in wireless communication technologies, Wireless Sensor Networks (WSNs) have gained attention worldwide in the past decade and are now being used in health monitoring, disaster management, defense, telecommunications, etc. Such networks are used in many industrial and consumer applications such as industrial process and environment monitoring, among others. A WSN network is a collection of specialized transducers known as sensor nodes with a communication link distributed randomly in any locations to monitor environmental parameters such as water level, and temperature. Each sensor node is equipped with a transducer, a signal processor, a power unit, and a transceiver. WSNs are now being widely used in the underground mining industry to monitor environmental parameters, including the amount of gas, water, temperature, humidity, oxygen level, dust, etc. The WSN for environment monitoring can be equivalently replaced by a multiple-input multiple-output (MIMO) relay network. Multi-hop relay networks have attracted significant research interest in recent years for their capability in increasing the coverage range. The network communication link from a source to a destination is implemented using the amplify-and-forward (AF) or decode-and-forward (DF) schemes. The AF relay receives information from the previous relay and simply amplifies the received signal and then forwards it to the next relay. On the other hand, the DF relay first decodes the received signal and then forwards it to the next relay in the second stage if it can perfectly decode the incoming signal. For analytical simplicity, in this thesis, we consider the AF relaying scheme and the results of this work can also be developed for the DF relay. The transceiver design for multi-hop MIMO relay is very challenging. This is because at the L-th relay stage, there are 2L possible channels. So, for a large scale network, it is not economical to send the signal through all possible links. Instead, we can find the best path from source-to-destination that gives the highest end-to-end signal-to-noise ratio (SNR). We can minimize the mean square error (MSE) or bit error rate (BER) objective function by sending the signal using the selected path. The set of relay in the path remains active and the rest of the relays are turned off which can save power to enhance network life-time. The best path signal transmission has been carried out in the literature for 2-hop MIMO relay and for multiple relaying it becomes very complex. In the first part of this thesis, we propose an optimal best path finding algorithm at perfect channel state information (CSI). We consider a parallel multi-hop multiple-input multiple-output (MIMO) AF relay system where a linear minimum mean-squared error (MMSE) receiver is used at the destination. We simplify the parallel network into equivalent series multi-hop MIMO relay link using best relaying, where the best relay ...
Richard, Vincent. "Multi-body optimization method for the estimation of joint kinematics : prospects of improvement." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1090/document.
Full textHuman movement analysis generally relies on skin markers monitoring techniques to reconstruct the joint kinematics. However, these acquisition techniques have important limitations including the "soft tissue artefacts" (i.e., the relative movement between the skin markers and the underlying bones). The multi-body optimization method aims to compensate for these artefacts by imposing the degrees of freedom from a predefined kinematic model to markers trajectories. The mechanical linkages typically used for modeling the joints however prevent a satisfactory estimate of the joint kinematics. This thesis addresses the prospects of improvement of the multi-body optimization method for the estimation of joint kinematics of the lower limb through different approaches: (1) the reconstruction of the kinematics by monitoring the angular velocity, the acceleration and the orientation of magneto-inertial measurement units instead of tracking markers, (2) the introduction of an elastic joint model based on the knee stiffness matrix, enabling a physiological estimation of joint kinematics and (3) the introduction of a "kinematic-dependent" soft tissue artefact model to assess and compensate for soft tissue artefact concurrently with estimating the joint kinematics. This work demonstrated the versatility of the multi-body optimization method. The results give hope for significant improvement in this method which is becoming increasingly used in biomechanics, especially for musculoskeletal modeling
Sharawi, Abeer Tarief. "OPTIMIZATION MODELS FOR EMERGENCY RELIEF SHELTER PLANNING FOR ANTICIPATED HURRICANE EVENTS." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4151.
Full textPh.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering PhD
Mori, Gerald M. "Sociotechnical systems analysis and design for selecting and designing the optimum manufacturing process." Master's thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-02162010-020334/.
Full textAndersson, Katarina. "Optimization of the Implantation Angle for a Talar Resurfacing Implant : A Finite Element Study." Thesis, KTH, Neuronik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-154237.
Full textFokala broskskador på talusbenet är den tredje vanligaste typen av fokala broskskador och kan ge upphov till smärta och instabilitet av fotleden. Episurf Medical AB är ett medicintekniskt företag som utvecklar individanpassade implantat för patienter med fokala broskskador. Episurf har nyligen påbörjat ett projekt där deras teknik ska användas i behandlingen av fokala broskskador på talusbenet. Den här masteruppsatsen var en del i Episurfs talusprojekt och dess huvudmål var att finna den optimala implantationsvinkeln av Episurfs implantat i behandlingen av fokala broskskador på talusbenet. Den optimala implanteringsvinkeln definierades som den vinkel som minimerade den effektiva von Mises-töjningen som verkade på implantatskaftet under stance-fasen i en normal gångcykel. Det är eftersträvansvärt att minimera belastningen på implantatskaftet eftersom en reducering av belastningen kan förbättra implantatets livslängd. En finita element-modell av en fotled behandlad med Episurfs implantat utvecklades för att för att finna den optimala implantationsvinkeln. I modellen placerades ett implantat med en diameter på 12 millimeter på mittendelen av talus mediala sida. En optimeringsalgoritm utformades för att finna implantationsvinkeln som minimerade den effektiva von Mises-töjningen på implantatskaftet. Den funna optimala implantationsvinkeln bestod av en vinkel på 12.5 grader i sagittalplan och en vinkel på 0 grader i koronalplan. Både storleken och riktningen på kraften som applicerats på fotleden under den simulerade stance-fasen av gångcykeln verkade påverka belastningen på implantatskaftet. Ett antal förenklingar har gjorts i projektets simuleringar, vilket kan påverka noggrannheten i resultatet. Därför rekommenderas att ytterligare, mer detaljerade simuleringar baserade på det här projektet görs för att förbättra resultatets noggrannhet.
Vennapusa, Siva Koti Reddy. "Design of bi-adhesive joint for optimal strength." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16675.
Full textSong, Ruoyu. "Game theoretic optimization for product line evolution." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54472.
Full textMazumdar, Anupam S. M. Massachusetts Institute of Technology. "Iterative algorithms for a joint pricing and inventory control problem with nonlinear demand functions." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/55076.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 79-81).
Price management, production planning and inventory control are important determinants of a firm's profitability. The intense competition brought about by rapid innovation, lean manufacturing time and the internet revolution has compelled firms to adopt a dynamic strategy that involves complex interplay between pricing and production decisions. In this thesis we consider some of these problems and develop computationally efficient algorithms that aim to tackle and optimally solve these problems in a finite amount of time. In the first half of the thesis we consider the joint pricing and inventory control problem in a deterministic and multiperiod setting utilizing the popular log linear demand model. We develop four algorithms that aim to solve the resulting profit maximization problem in a finite amount of time. The developed algorithms are then tested in a variety of settings ranging from small to large instances of trial data. The second half of the thesis deals with setting prices effectively when the customer demand is assumed to follow the multinomial logit demand model, which is the most popular discrete choice demand model. The profit maximization problem (even in the absence of constraints) is non-convex and hard to solve. Despite this fact we develop algorithms that compute the optimal solution efficiently. We test the algorithms we develop in a wide variety of scenarios from small to large customer segment, with and without production/inventory constraints. The last part of the thesis develops solution methods for the joint pricing and inventory control problem when costs are linear and demand follows the multinomial logit model.
by Anupam Mazumdar.
S.M.
Buchal, Ralph Oliver. "Determination of robot trajectories satisfying joint limit and interference constraints using an optimization method." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26967.
Full textApplied Science, Faculty of
Mechanical Engineering, Department of
Graduate
Colpo, Kristie M. "Joint Sensing/Sampling Optimization for Surface Drifting Mine Detection with High-Resolution Drift Model." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17345.
Full textEvery mine countermeasures (MCM) operation is a balance of time versus risk. In attempting to reduce time and risk, it is in the interest of the MCM community to use unmanned, stationary sensors to detect and monitor drifting mines through harbor inlets and straits. A network of stationary sensors positioned along an area of interest could be critical in such a process by removing the MCM warfighter from a threat area and reducing the time required to detect a moving target. Although many studies have been conducted to optimize sensors and sensor networks for moving target detection, few of them considered the effects of the environment. In a drifting mine scenario, an oceanographic drift model could offer an estimation of surrounding environmental effects and therefore provide time critical estimations of target movement. These approximations can be used to further optimize sensor network components and locations through a defined methodology using estimated detection probabilities. The goal of this research is to provide such a methodology by modeling idealized stationary sensors and surface drift for the Hampton Roads Inlet.
Cizaire, Claire (Claire Jia Ling). "Optimization models for joint airline pricing and seat inventory control : multiple products, multiple periods." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/72842.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 153-157).
Pricing and revenue management are two essential levers to optimize the sales of an airline's seat inventory and maximize revenues. Over the past few decades, they have generated a great deal of research but have typically been studied and optimized separately. On the one hand, the pricing process focused on demand segmentation and optimal fares, regardless of any capacity constraints. On the other hand, researchers in revenue management developed algorithms to set booking limits by fare product, given a set of fares and capacity constraints. This thesis develops several approaches to solve for the optimal fares and booking limits jointly and simultaneously. The underlying demand volume in an airline market is modeled as a function of the fares. We propose an initial approach to the two-product, two-period revenue optimization problem by first assuming that the demand is deterministic. We show that the booking limit on sales of the lower-priced product is unnecessary in this case, allowing us to simplify the optimization problem. We then develop a stochastic optimization model and analyze the combined impacts of fares and booking limits on the total number of accepted bookings when the underlying demand is uncertain. We demonstrate that this joint optimization approach can provide a 3-4% increase in revenues from a traditional pricing and revenue management practices. The stochastic model is then extended to the joint pricing and seat inventory control optimization problem for booking horizons involving more than two booking periods, as is the case in reality. A generalized methodology for optimization is presented, and we show that the complexity of the joint optimization problem increases substantially with the number of booking periods. We thus develop three heuristics. Simulations for a three-period problem show that all heuristics outperform the deterministic optimization model. In addition, two of the heuristics can provide revenues close to those obtained with the stochastic model. This thesis provides a basis for the integration of pricing and revenue management. The combined effects of fares and booking limits on the number of accepted bookings, and thus on the revenues, are explicitly taken into account in our joint optimization models. We showed that the proposed approaches can further enhance revenues.
by Claire Cizaire.
Ph.D.
Guan, Kyle Chi. "Cost-effective optical network architecture : a joint optimization of topology, switching, routing and wavelength assignment." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/38678.
Full textIncludes bibliographical references (p. 279-285).
To provide end users with economic access to high bandwidth, the architecture of the next generation metropolitan area networks (MANs) needs to be judiciously designed from the cost perspective. In addition to a low initial capital investment, the ultimate goal is to design networks that exhibit excellent scalability - a decreasing cost-per-node-per-unit-traffic as user number and transaction size increase. As an effort to achieve this goal, in this thesis we search for the scalable network architectures over the solution space that embodies the key aspects of optical networks: fiber connection topology, switching architecture selection and resource dimensioning, routing and wavelength assignment (RWA). Due to the inter-related nature of these design elements, we intended to solve the design problem jointly in the optimization process in order to achieve over-all good performance. To evaluate how the cost drives architectural tradeoffs, an analytical approach is taken in most parts of the thesis by first focusing on networks with symmetric and well defined structures (i.e., regular networks) and symmetric traffic patterns (i.e., all-to-all uniform traffic), which are fair representations that give us suggestions of trends, etc.
(cont.) We starts with a examination of various measures of regular topologies. The average minimum hop distance plays a crucial role in evaluating the efficiency of network architecture. From the perspective of designing optical networks, the amount of switching resources used at nodes is proportional to the average minimum hop distance. Thus a smaller average minimum hop distance translates into a lower fraction of pass-through traffic and less switching resources required. Next, a first-order cost model is set up and an optimization problem is formulated for the purpose of characterizing the tradeoffs between fiber and switching resources. Via convex optimization techniques, the joint optimization problem is solved analytically for (static) uniform traffic and symmetric networks. Two classes of regular graphs - Generalized Moore Graphs and A-nearest Neighbors Graphs - are identified to yield lower and upper cost bounds, respectively. The investigation of the cost scalability further demonstrates the advantage of the Generalized Moore Graphs as benchmark topologies: with linear switching cost structure, the minimal normalized cost per unit traffic decreases with increasing network size for the Generalized Moore Graphs and their relatives.
(cont.) In comparison, for less efficient fiber topologies (e.g., A-nearest Neighbors) and switching cost structures (e.g., quadratic cost), the minimal normalized cost per unit traffic plateaus or even increases with increasing network size. The study also reveals other attractive properties of Generalized Moore Graphs in conjunction with minimum hop routing - the aggregate network load is evenly distributed over each fiber. Thus, Generalized Moore Graphs also require the minimum number of wavelengths to support a given uniform traffic demand. Further more, the theoretical works on the Generalized Moore Graphs and their close relatives are extended to study more realistic design scenarios in two aspects. One aspect addresses the irregular topologies and (static) non-uniform traffic, for which the results of Generalized Moore networks are used to provide useful estimates of network cost, and are thus offering good references for cost-efficient optical networks. The other aspect deals with network design under random demands. Two optimization formulations that incorporate the traffic variability are presented.
(cont.) The results show that as physical architecture, Generalized Moore Graphs are most robust (in cost) to the demand uncertainties. Analytical results also provided design guidelines on how optimum dimensioning, network connectivity, and network costs vary as functions of risk aversion, service level requirements, and probability distributions of demands.
by Kyle Chi Guan.
Ph.D.
Kadaikar, Aysha-Khatoon. "Optimization of the Rate-Distortion Compromise for Stereoscopic Image Coding using Joint Entropy-Distortion Metric." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCD083/document.
Full textDuring the last decades, a wide range of applications using stereoscopic technology has emerged still offering an increased immersion to the users such as video games with autostereoscopic displays, 3D-TV or stereovisio-conferencing. The raise of these applications requires fast processing and efficient compression techniques. In particular, stereoscopic images require twice the amount of information needed to transmit or store them in comparison with 2D images as they are composed of two views of the same scene. The contributions of our work are in the field of stereoscopic image compression and more precisely, we get interested in the improvement of the disparity map estimation. Generally, disparities are selected by minimizing a distortion metric which is sometimes subjected to a smoothness constraint, assuming that a smooth disparity map needs a smaller bitrate to be encoded. But a smoother disparity map does not always reduce significantly the bitrate needed to encode it but can increase the distortion of the predicted view. Therefore, the first algorithm we have proposed minimizes a joint entropy-distortion metric to select the disparities. At each step of the algorithm, the bitrate of the final disparity map is estimated and included in the metric to minimize. Moreover, this algorithm relies on a tree where a fixed number of paths are extended at each depth of the tree, ensuring good rate-distortion performance. In the second part of the work, we have proposed a sub-optimal solution with a smaller computational complexity by considering an initial solution -the one minimizing the distortion of the predicted view- which is successively modified as long as an improvement is observed in terms of rate-distortion. Then, we have studied how to take advantages of large search areas in which the disparities are selected as one can easily supposed that enlarging the search area will increase the distortion performance as there will be more choices of disparities. In the other hand, the larger is the range of the selected disparities, the higher is supposed to be the cost of the disparity map in terms of bitrate. We have proposed two approaches allowing to take advantage of a large search area by selecting only sets of disparities belonging to it enabling to achieve a given bitrate while minimizing the distortion of the predicted image. The last part of the work concerns variable block sizes which undeniably allows to improve the bitrate-distortion performance as the block size suits to the image features. We have thus proposed a novel algorithm which jointly estimates and optimizes the disparity and the block length maps
Chatzitheodoridi, Maria-Elisavet. "Processing Optimization for Continuous Phase Modulation-based Joint Radar-Communication System : Application on Imaging Radar." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPAST022.
Full textDue to the continuous growth of electromagnetic applications, the spectrum gets more and more congested. A possible solution to this problem is the creation of joint radar-communication systems, because they can alleviate the spectrum occupancy by using the same bandwidth to perform both applications. In this thesis, a joint Synthetic Aperture Radar (SAR)-Communication system based on a communication waveform is considered. To do so, among all the existing codes, we chose Continuous Phase Modulated codes (CPM), and more specifically a sub-family called Phase Frequency Shift-Keying codes (CPFSK). Their properties, in particular the spectral occupation, are first studied and compared to other well-known communication codes. However, these waveforms present degraded compression qualities when compared to the usual chirp used for radars. More specifically, the sidelobes generated from the Matched Filter compression are higher, and thus deteriorate the resulting SAR image. The mismatched filter that minimizes the sidelobe level is proposed along with a fast algorithm that provides the filters for all the transmitted signals during an acceptable computational cost. This mismatched filter is further improved so that it can deal with unknown parameters. More precisely, if unknown Doppler shift or off-grid delay values are applied to the received signal, then an improved mismatched filter is provided. Such a problem can be extended to other radar applications. Once the range compression method choice is established, an evaluation of the results is proposed. On the one hand, re-synthesized SAR images are generated, reconstructed from real chirp-based data, using CPM codes and mismatched filters, and different comparison tools to ensure their performance.On the other hand, real data are acquired in an ISAR framework, in order to validate our system in a realistic context. Finally, we can provide a positive answer to the question: can we create a joint SAR-communication system that transmits information and provides an image of good radar quality?
Grenville, N. Delia. "A Sociotechnical Approach to Evaluating the Effects of Managerial Time Allotment on Department Performance." Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36811.
Full textMaster of Science
IRFAN, MUHAMMAD ABEER. "Joint geometry and color denoising for 3D point clouds." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2912976.
Full textGecili, Hakan. "Joint Shelf Design and Shelf Space Allocation Problem for Retailers." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1594374475655644.
Full textTeague, Kory Alan. "Approaches to Joint Base Station Selection and Adaptive Slicing in Virtualized Wireless Networks." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/85966.
Full textMaster of Science
5G, the next generation cellular network standard, promises to provide significant improvements over current generation standards. For 5G to be successful, this must be accompanied by similarly significant efficiency improvements. Wireless network virtualization is a promising technology that has been shown to improve the cost efficiency of current generation cellular networks. By abstracting the physical resource—such as cell tower base stations— from the use of the resource, virtual resources are formed. This work investigates the problem of selecting virtual resources (e.g., base stations) to construct virtual wireless networks with minimal cost and slicing the selected resources to individual networks to optimally satisfy individual network demands. This problem is framed in a stochastic optimization framework and two approaches are presented for approximation. The first approach converts the framework into a deterministic equivalent and reduces it to a tractable form. The second approach uses a genetic algorithm to approximate resource selection. Approaches are simulated and evaluated utilizing a demand model constructed to emulate the statistics of an observed real world urban network. Simulations indicate that the first approach can provide a reasonably tight solution with significant time expense, and that the second approach provides a solution in significantly less time with the introduction of marginal error.
Camacho, Torregrosa Esteban Efraím. "Dosage optimization and bolted connections for UHPFRC ties." Doctoral thesis, Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/34790.
Full textCamacho Torregrosa, EE. (2013). Dosage optimization and bolted connections for UHPFRC ties [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34790
TESIS
Coursen, Jeffrey Thomas. "An experiment in joint product price optimization price elasticities and subsitution [sic] decisions of the hungry barfly /." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1202498978/.
Full textSILVA, ALEXANDRE MOREIRA DA. "TWO-STAGE ROBUST OPTIMIZATION MODELS FOR POWER SYSTEM OPERATION AND PLANNING UNDER JOINT GENERATION AND TRANSMISSION SECURITY CRITERIA." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24754@1.
Full textCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Recentes apagões em todo o mundo fazem da confiabilidade de sistemas de potência, no tocante a contingências múltiplas, um tema de pesquisa mundial. Dentro desse contexo, se faz importante investigar métodos eficientes de proteger o sistema contra falhas de alguns de seus componentes, sejam elas dependentes e/ou independentes de outras falhas. Nesse sentido, se tornou crucial a incorporação de critérios de segurança mais rigorosos na operação e planejamento de sistemas de potência. Contingências múltiplas são mais comuns e desastrosas do que falhas naturais e independentes. A principal razão para isso reside na complexidade da estabilidade dinâmica de sistemas de potência. Além disso, o sistema de proteção que opera em paralelo ao sistema de distribuição não é livre de falhas. Portanto, interrupções naturais podem causar contingências em cascata em decorrência do mau funcionamento de mecanismos de proteção ou da instabilidade do sistema elétrico como um todo. Nesse contexto, se dá a motivação pela busca de critérios de segurança mais severos como, por exemplo, o n - K, onde K pode ser maior do que 2. Nesse trabalho, o principal objetivo é incorporar o crtitério de segurança geral n-K para geração e transmissão em modelos de operação e planejamento de sistemas de potência. Além de interrupções em geradores, restrições de rede, bem como falhas em linhas de transmiss˜ao também são modeladas. Esse avanço leva a novos desafios computacionais, para os quais formulamos metodologias de solução eficientes baseadas em decomposição de Benders. Considerando operação, duas abordagens são apresentadas. A primeira propõe um modelo de otimização trinível para decidir o despacho ótimo de energia e reservas sob um critério de segurançaa n - K. Nessa abordagem, a alta dimensionalidade do problema, por contemplar restrições de rede, bem como falhas de geradores e de linhas de transmissão, é contornada por meio da implícita consideração do conjunto de possíveis contingências. No mesmo contexto, a segunda abordagem leva em conta a incerteza da carga a ser suprida e a correlação entre demandas de diferentes barras. Considerando planejamento de expansão da transmissão, outro modelo de otimização trinível é apresentado no intuito de decidir quais linhas de transmissão, dentro de um conjunto de candidatas, devem ser construídas para atender a um critério de segurança n - K e, consequentemente, aumentar a confiabilidade do sistema como um todo. Portanto, as principais contribuições do presente trabalho são as seguintes: 1) modelos de otimização trinível para considerar o critério de segurança n - K em operação e planejamento de sistemas de potência, 2) consideração implícita de todo o conjunto de contingências por meio de uma abordagem de otimização robusta ajustável, 3) otimização conjunta de energia e reserva para operação de sistemas de potência, considerando restrições de rede e garantindo a entregabilidade das reservas em todos os estados pós-contingência considerados, 4) metodologias de solução eficientes baseadas em decomposição de Benders que convergem em passos finitos para o ótimo global e 5) desenvolvimento de restrições válidas que alavancam a eficiência computacional. Estudos de caso ressaltam a eficácia das metodologias propostas em capturar os efeitos econômicos de demanda nodal correlacionada sob um critério de segurançaa n - 1, em reduzir o esfor¸co computacional para considerar os critérios de seguran¸ca convencionais n-1 e n-2 e em considerar critérios de segurança mais rigorosos do que o n - 2, um problema intratável até então.
Recent major blackouts all over the world have been a driving force to make power system reliability, regarding multiple contingencies, a subject of worldwide research. Within this context, it is important to investigate efficient methods of protecting the system against dependent and/or independent failures. In this sense, the incorporation of tighter security criteria in power systems operation and planning became crucial. Multiple contingencies are more common and dangerous than natural independent faults. The main reason for this lies in the complexity of the dynamic stability of power systems. In addition, the protection system, that operates in parallel to the supply system, is not free of failures. Thus, natural faults can cause subsequent contingencies (dependent on earlier contingencies) due to the malfunction of the protection mechanisms or the instability of the overall system. These facts drive the search for more stringent safety criteria, for example, n - K, where K can be greater than 2. In the present work, the main objective is to incorporate the joint generation and transmission general security criteria in power systems operation and planning models. Here, in addition to generators outages, network constraints and transmission lines failures are also accounted for. Such improvement leads to new computational challenges, for which we design efficient solution methodologies based on Benders decomposition. Regarding operation, two approaches are presented. The first one proposes a trilevel optimization model to decide the optimal scheduling of energy and reserve under an n - K security criterion. In such approach, the high dimensionality curse of considering network constraints as well as outages of generators and transmission assets is withstood by implicitly taking into account the set of possible contingencies. The second approach includes correlated nodal demand uncertainty in the same framework. Regarding transmission expansion planning, another trilevel optimization model is proposed to decide which transmission assets should be built within a set of candidates in order to meet an n - K security criterion, and, consequently, boost the power system reliability. Therefore, the main contributions of this work are the following: 1) trilevel models to consider general n - K security criteria in power systems operation and planning, 2) implicit consideration of the whole contingency set by means of an adjustable robust optimization approach, 3) co-optimization of energy and reserves for power systems operation, regarding network constraints and ensuring the deliverability of reserves in all considered post-contingency states, 4) efficient solution methodologies based on Benders decomposition that finitely converges to the global optimal solution, and 5) development of valid constraints to boost computational efficiency. Case studies highlight the effectiveness of the proposed methodologies in capturing the economic effect of nodal demand correlation on power system operation under an n - 1 security criterion, in reducing the computational effort to consider conventional n-1 and n-2 security criteria, and in considering security criteria tighter than n - 2, an intractable problem heretofore.
Watanabe, Tetsuyou. "Optimization of grasping by a robotic hand and trajectory design of 3-D.O.F. arm with an unactuated joint." 京都大学 (Kyoto University), 2003. http://hdl.handle.net/2433/148855.
Full textAsseln, Malte [Verfasser], Klaus [Akademischer Betreuer] Radermacher, and Dieter Christian [Akademischer Betreuer] Wirtz. "Morphological and functional analysis of the knee joint for implant design optimization / Malte Asseln ; Klaus Radermacher, Dieter Christian Wirtz." Aachen : Universitätsbibliothek der RWTH Aachen, 2019. http://d-nb.info/1221099043/34.
Full textMoety, Farah. "Joint minimization of power and delay in wireless access networks." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S108/document.
Full textIn wireless access networks, one of the most recent challenges is reducing the power consumption of the network, while preserving the quality of service perceived by the end users. The present thesis provides solutions to this challenging problem considering two objectives, namely, saving power and minimizing the transmission delay. Since these objectives are conflicting, a tradeoff becomes inevitable. Therefore, we formulate a multi-objective optimization problem with aims of minimizing the network power consumption and transmission delay. Power saving is achieved by adjusting the operation mode of the network Base Stations (BSs) from high transmit power levels to low transmit levels or even sleep mode. Minimizing the transmission delay is achieved by selecting the best user association with the network BSs. We cover two different wireless networks, namely IEEE 802.11 wireless local area networks and LTE cellular networks
畔上, 秀幸, Hideyuki AZEGAMI, 悟史 小山, and Satoshi KOYAMA. "規定した変形を生む異種材料境界面の形状設計." 日本機械学会, 2005. http://hdl.handle.net/2237/12187.
Full textCheng, Jianqiang. "Stochastic Combinatorial Optimization." Thesis, Paris 11, 2013. http://www.theses.fr/2013PA112261.
Full textIn this thesis, we studied three types of stochastic problems: chance constrained problems, distributionally robust problems as well as the simple recourse problems. For the stochastic programming problems, there are two main difficulties. One is that feasible sets of stochastic problems is not convex in general. The other main challenge arises from the need to calculate conditional expectation or probability both of which are involving multi-dimensional integrations. Due to the two major difficulties, for all three studied problems, we solved them with approximation approaches.We first study two types of chance constrained problems: linear program with joint chance constraints problem (LPPC) as well as maximum probability problem (MPP). For both problems, we assume that the random matrix is normally distributed and its vector rows are independent. We first dealt with LPPC which is generally not convex. We approximate it with two second-order cone programming (SOCP) problems. Furthermore under mild conditions, the optimal values of the two SOCP problems are a lower and upper bounds of the original problem respectively. For the second problem, we studied a variant of stochastic resource constrained shortest path problem (called SRCSP for short), which is to maximize probability of resource constraints. To solve the problem, we proposed to use a branch-and-bound framework to come up with the optimal solution. As its corresponding linear relaxation is generally not convex, we give a convex approximation. Finally, numerical tests on the random instances were conducted for both problems. With respect to LPPC, the numerical results showed that the approach we proposed outperforms Bonferroni and Jagannathan approximations. While for the MPP, the numerical results on generated instances substantiated that the convex approximation outperforms the individual approximation method.Then we study a distributionally robust stochastic quadratic knapsack problems, where we only know part of information about the random variables, such as its first and second moments. We proved that the single knapsack problem (SKP) is a semedefinite problem (SDP) after applying the SDP relaxation scheme to the binary constraints. Despite the fact that it is not the case for the multidimensional knapsack problem (MKP), two good approximations of the relaxed version of the problem are provided which obtain upper and lower bounds that appear numerically close to each other for a range of problem instances. Our numerical experiments also indicated that our proposed lower bounding approximation outperforms the approximations that are based on Bonferroni's inequality and the work by Zymler et al.. Besides, an extensive set of experiments were conducted to illustrate how the conservativeness of the robust solutions does pay off in terms of ensuring the chance constraint is satisfied (or nearly satisfied) under a wide range of distribution fluctuations. Moreover, our approach can be applied to a large number of stochastic optimization problems with binary variables.Finally, a stochastic version of the shortest path problem is studied. We proved that in some cases the stochastic shortest path problem can be greatly simplified by reformulating it as the classic shortest path problem, which can be solved in polynomial time. To solve the general problem, we proposed to use a branch-and-bound framework to search the set of feasible paths. Lower bounds are obtained by solving the corresponding linear relaxation which in turn is done using a Stochastic Projected Gradient algorithm involving an active set method. Meanwhile, numerical examples were conducted to illustrate the effectiveness of the obtained algorithm. Concerning the resolution of the continuous relaxation, our Stochastic Projected Gradient algorithm clearly outperforms Matlab optimization toolbox on large graphs
Potvin, Brigitte. "Predicting Muscle Activations in a Forward-Inverse Dynamics Framework Using Stability-Inspired Optimization and an In Vivo-Based 6DoF Knee Joint." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34647.
Full textLourens, Spencer. "Bias in mixtures of normal distributions and joint modeling of longitudinal and time-to-event data with monotonic change curves." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/1685.
Full textLiu, Penghuan. "Statistical and numerical optimization for speckle blind structured illumination microscopy." Thesis, Ecole centrale de Nantes, 2018. http://www.theses.fr/2018ECDN0008/document.
Full textConventional structured illumination microscopy (SIM) can surpass the resolution limit inoptical microscopy caused by the diffraction effect, through illuminating the object with a set of perfectly known harmonic patterns. However, controlling the illumination patterns is a difficult task. Even worse, strongdistortions of the light grid can be induced by the sample within the investigated volume, which may give rise to strong artifacts in SIM reconstructed images. Recently, blind-SIM strategies were proposed, whereimages are acquired through unknown, non-harmonic,speckle illumination patterns, which are much easier to generate in practice. The super-resolution capacity of such approaches was observed, although it was not well understood theoretically. This thesis presents two new reconstruction methods in SIM using unknown speckle patterns (blind-speckle-SIM): one joint reconstruction approach and one marginal reconstruction approach. In the joint reconstruction approach, we estimate the object and the speckle patterns together by considering a basis pursuit denoising (BPDN) model with lp,q-norm regularization, with p=>1 and 0
ALJhayyish, Anwer K. "Optimizing Slab Thickness and Joint Spacing for Long-Life Concrete Pavement in Ohio." Ohio University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1550099928352708.
Full textWang, Lu. "Nonnegative joint diagonalization by congruence for semi-nonnegative independent component analysis." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S141/document.
Full textThe Joint Diagonalization of a set of matrices by Congruence (JDC) appears in a number of signal processing problems, such as in Independent Component Analysis (ICA). Recent developments in ICA under the nonnegativity constraint of the mixing matrix, known as semi-nonnegative ICA, allow us to obtain a more realistic representation of some real-world phenomena, such as audios, images and biomedical signals. Consequently, during this thesis, the main objective was not only to design and develop semi-nonnegative ICA methods based on novel nonnegative JDC algorithms, but also to illustrate their interest in applications involving Blind Source Separation (BSS). The proposed nonnegative JDC algorithms belong to two fundamental strategies of optimization. The first family containing five algorithms is based on the Jacobi-like optimization. The nonnegativity constraint is imposed by means of a square change of variable, leading to an unconstrained problem. The general idea of the Jacobi-like optimization is to factorize the matrix variable as a product of a sequence of elementary matrices which is defined by only one parameter, then to estimate these elementary matrices one by one in a specific order. The second family containing one algorithm is based on the alternating direction method of multipliers. Such an algorithm is derived by successively minimizing the augmented Lagrangian function of the cost function with respect to the variables and the multipliers. Experimental results on simulated matrices show a better performance of the proposed algorithms in comparison with several classical JDC methods, which do not use the nonnegativity as constraint prior. It appears that our methods can achieve a better estimation accuracy particularly in difficult contexts, for example, for a low signal-to-noise ratio, a small number of input matrices and a high coherence level of matrix. Then we show the interest of our approaches in solving real-life problems. To name a few, we are interested in i) the analysis of the chemical compounds in the magnetic resonance spectroscopy, ii) the identification of the harmonically fixed spectral profiles (such as piano notes) of a piece of signal-channel music record by decomposing its spectrogram, iii) the partial removal of the show-through effect of digital images, where the show-through effect were caused by scanning a semi-transparent paper. These applications demonstrate the validity and improvement of our algorithms, comparing with several state-of-the-art BSS methods