Relevant bibliographies by topics / SDP optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'SDP optimization'

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Published: 25 May 2024

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Journal articles on the topic "SDP optimization"

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MEVISSEN, MARTIN, and MASAKAZU KOJIMA. "SDP RELAXATIONS FOR QUADRATIC OPTIMIZATION PROBLEMS DERIVED FROM POLYNOMIAL OPTIMIZATION PROBLEMS." Asia-Pacific Journal of Operational Research 27, no. 01 (February 2010): 15–38. http://dx.doi.org/10.1142/s0217595910002533.

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Based on the convergent sequence of SDP relaxations for a multivariate polynomial optimization problem (POP) by Lasserre (2006), Waki et al. (2006) constructed a sequence of sparse SDP relaxations to solve sparse POPs efficiently. Nevertheless, the size of the sparse SDP relaxation is the major obstacle in order to solve POPs of higher degree. This paper proposes an approach to transform general POPs to quadratic optimization problems (QOPs), which allows to reduce the size of the SDP relaxation substantially. We introduce different heuristics resulting in equivalent QOPs and show how sparsity of a POP is maintained under the transformation procedure. As the most important issue, we discuss how to increase the quality of the SDP relaxation for a QOP. Moreover, we increase the accuracy of the solution of the SDP relaxation by applying additional local optimization techniques. Finally, we demonstrate the high potential of this approach through numerical results for large scale POPs of higher degree.
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Liu, Yiyuan, Baoguo Li, and Yizhou Yao. "Radar-Embedded Communication Waveform Design Based on Parameter Optimization." Journal of Physics: Conference Series 2404, no. 1 (December 1, 2022): 012032. http://dx.doi.org/10.1088/1742-6596/2404/1/012032.

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Abstract Radar-embedded communication (REC) is a low probability of intercept (LPI) communication method that enables radar and communication to share the spectrum. Covert communication is accomplished by embedding low-power communication waveforms in high-power radar backscatter echoes. This research, by optimizing the eigenvalue matrix power exponent a of the shaped dominant projection (SDP) waveform, proposes an SDP waveform with variable eigenvalue matrix power exponent, namely SDP-a waveform. Then, the reliability of waveform communication and LPI performance are theoretically analyzed by processing gain. Finally, the simulation experiments are carried out with SDP-0.25, SDP-0.5, and SDP-0.75 waveforms as examples. The experimental results are consistent with the theoretical analysis results, indicating that the optimization of the eigenvalue matrix power exponent can meet the performance requirements of different aspects.
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Metzlaff, Tobias. "Symmetry Adapted Bases for Trigonometric Optimization." ACM Communications in Computer Algebra 57, no. 3 (September 2023): 137–40. http://dx.doi.org/10.1145/3637529.3637535.

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We present an algorithm to compute the global minimum of a trigonometric polynomial, when it is invariant under the exponential action of a Weyl group. This is based on a common relaxation technique that leads to a semi-definite program (SDP). It is then shown how to exploit the invariance in order to reduce the number of variables of the SDP and to simplify its structure significantly. This approach complements the one that was proposed as a poster at the recent ISSAC 2022 conference [HMMR22] and later extended to [HMMR23]. In the previous work, we first used the invariance of the objective function to obtain a classical polynomial optimization problem on the orbit space and subsequently relaxed the problem to an SDP. In the present work, we first apply the relaxation and then exploit symmetry. We show that the Weyl group action is induced by an orthogonal representation and describe its isotypic decomposition.
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Hu, En-Liang, and Bo Wang. "A new optimization in SDP-based learning." Neurocomputing 365 (November 2019): 10–20. http://dx.doi.org/10.1016/j.neucom.2019.06.058.

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Hu, Haijiang, Shaojing Song, and Fengdeng Zhang. "FIR to FIR Model Reduction with Linear Group Delay in Passband by SDP Optimization." Journal of Electrical and Computer Engineering 2020 (February 20, 2020): 1–7. http://dx.doi.org/10.1155/2020/4503706.

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Filter model reduction is an important optimization method in digital signal processing. A method of FIR to FIR model reduction using SDP optimization is proposed in this paper. At first, we use SDP to design an original FIR filter. Then we name a general K-order FIR digital filter H1z−1 with coefficient values equal to the first K + 1 filter coefficient values of H0z−1. Finally, we design a new general K-order FIR digital filter H2z−1 connected in parallel with H1z−1 using SDP optimization. The experiment results show this method has good performance on the magnitude error and the linear phase in passband. Therefore, this method can be used in the field of digital signal processing.
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KANNO, Y., M. OHSAKI, and N. KATOH. "SEQUENTIAL SEMIDEFINITE PROGRAMMING FOR OPTIMIZATION OF FRAMED STRUCTURES UNDER MULTIMODAL BUCKLING CONSTRAINTS." International Journal of Structural Stability and Dynamics 01, no. 04 (December 2001): 585–602. http://dx.doi.org/10.1142/s0219455401000305.

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An algorithm based on Semi-Definite Programming (SDP) formulation is proposed for optimum design of structures for specified linear buckling load factors. Optimal trusses and frames are computed by using the primal-dual interior-point method based on SDP scheme. It is well known that optimizing structures under buckling constraints is difficult because of the non-differentiability of buckling load factors for the case of multimodal solutions. The examples studied indicate that optimum designs with multiple buckling load factors can be found with no difficulty by successively solving the SDP problems.
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Gil-González, Walter, Alexander Molina-Cabrera, Oscar Danilo Montoya, and Luis Fernando Grisales-Noreña. "An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum." Applied Sciences 10, no. 21 (October 30, 2020): 7681. http://dx.doi.org/10.3390/app10217681.

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This paper deals with a classical problem in power system analysis regarding the optimal location and sizing of distributed generators (DGs) in direct current (DC) distribution networks using the mathematical optimization. This optimization problem is divided into two sub-problems as follows: the optimal location of DGs is a problem, with those with a binary structure being the first sub-problem; and the optimal sizing of DGs with a nonlinear programming (NLP) structure is the second sub-problem. These problems originate from a general mixed-integer nonlinear programming model (MINLP), which corresponds to an NP-hard optimization problem. It is not possible to provide the global optimum with conventional programming methods. A mixed-integer semidefinite programming (MI-SDP) model is proposed to address this problem, where the binary part is solved via the branch and bound (B&B) methods and the NLP part is solved via convex optimization (i.e., SDP). The main advantage of the proposed MI-SDP model is the possibility of guaranteeing a global optimum solution if each of the nodes in the B&B search is convex, as is ensured by the SDP method. Numerical validations in two test feeders composed of 21 and 69 nodes demonstrate that in all of these problems, the optimal global solution is reached by the MI-SDP approach, compared to the classical metaheuristic and hybrid programming models reported in the literature. All the simulations have been carried out using the MATLAB software with the CVX tool and the Mosek solver.
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Ren, Fangyu, Huotao Gao, Lijuan Yang, and Sang Zhou. "Distributed Multistatic Sky-Wave Over-the-Horizon Radar’s Positioning Algorithm for the Marine Target." International Journal of Antennas and Propagation 2021 (October 27, 2021): 1–7. http://dx.doi.org/10.1155/2021/1028784.

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This paper establishes a distributed multistatic sky-wave over-the-horizon radar (DMOTHR) model and proposes a semidefinite relaxation positioning (SDP) algorithm to locate marine ship targets. In the DMOTHR, it is difficult to locate the target due to the complexity of the signal path propagation. Therefore, this paper uses the ionosphere as the reflector to convert the propagation path from a polyline to a straight line for establishing the model, and then the SDP algorithm will be used to transform a highly nonlinear positioning optimization problem into a convex optimization problem. Finally, it is concluded through the simulations that the SDP algorithm can obtain better positioning accuracy under a certain Doppler frequency error and ionospheric measurement error.
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Nandyala, Raja Thejaswini, and Muthupandi Gandhi. "High uncertainty aware localization and error optimization of mobile nodes for wireless sensor networks." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 4 (December 1, 2023): 2022. http://dx.doi.org/10.11591/ijai.v12.i4.pp2022-2032.

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<p>The localization of mobile sensor nodes in a wireless sensor network (WSN) is a key research area for the speedy development of wireless communication and microelectronics. The localization of mobile sensor nodes massively depends upon the received signal strength (RSS). Recently, the least squared relative error (LSRE) measurements are optimized using traditional semidefinite programming (SDP) and the location of the mobile sensor nodes was determined using the previous localization methods like least squared relative error and semidefinite programming (LSRE-SDP), and approximate nonlinear least squares and semidefinite programming (ANLS-SDP). Therefore, in this work, a novel high uncertainty aware-localization error correction and optimization (HUA-LECO) model is employed to minimize the aforementioned problems regarding the localization of mobile sensor nodes and enhance the performance efficiency of root mean square error (RMSE) results. Here, the position of target mobile sensor nodes is evaluated based on the gathered measurements while discarding faulty data. Here, an iterative weight updation approach is utilized to perform localization based on Monte Carlo simulations. Simulation results show significant improvement in terms of RMSE results in comparison with traditional LSRE-SDP and ANLS-SDP methods under high uncertainty.</p>
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Guolei, Tang, Zhou Huicheng, and Li Ningning. "Reservoir optimization model incorporating inflow forecasts with various lead times as hydrologic state variables." Journal of Hydroinformatics 12, no. 3 (November 24, 2009): 292–302. http://dx.doi.org/10.2166/hydro.2009.088.

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This paper presents two Stochastic Dynamic Programming models (SDP) to investigate the potential value of inflow forecasts with various lead times in hydropower generation. The proposed SDP frameworks generate hydropower operating policies for the Ertan hydropower station, China. The objective function maximizes the total hydropower generation with the firm capacity committed for the system. The two proposed SDP-derived operating policies are simulated using historical inflows, as well as inflow forecasts with various lead times. Four performance indicators are chosen to assist in selecting the best reservoir operating policy: mean annual hydropower production, Nash–Sutcliffe sufficiency score, reliability and vulnerability. Performances of the proposed SDP-derived policies are compared with those of other existing policies. The simulation results demonstrate that including inflow forecasts with various lead times is beneficial to the Ertan hydropower generation, and the chosen operating policy cannot only yield higher hydropower production, but also produces reasonable storage hydrographs effectively.
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Dissertations / Theses on the topic "SDP optimization"

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Campos, Salazar Juan. "A multigrid approach to SDP relaxations of sparse polynomial optimization problems." Thesis, Imperial College London, 2017. http://hdl.handle.net/10044/1/56630.

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We propose two multigrid approaches for the global optimization of polynomial op- timization problems. In our first contribution we consider problems that arise from the discretization of infinite dimensional optimization problems, such as PDE optimiza- tion problems, boundary value problems and some global optimization applications. In many of these applications, the level of discretization can be used to obtain a hierarchy of optimization models that captures the underlying infinite dimensional problem at different degrees of fidelity. This approach, inspired by multigrid methods, has been successfully used for decades to solve large systems of linear equations. However, it has not been adapted to SDP relaxations of polynomial optimization problems. The main difficulty is that the geometric information between grids is lost when the original problem is approximated via an SDP relaxation. Despite the loss of geometric infor- mation, we show how a multigrid approach can be applied by developing prolongation operators to relate the primal and dual variables of the SDP relaxation between lower and higher levels in the hierarchy of discretizations. We develop sufficient conditions for the operators to be useful in applications. Our conditions are easy to verify in prac- tice, and we discuss how they can be used to reduce the complexity of infeasible interior iv point methods. Following the same reasoning, the second approach does not assume any particular structure of the underlying polynomial problem, but instead considers the hierarchy of sparse SDP relaxations that can be obtained for any unconstrained polynomial optimizations problem with structured sparsity. Prolongation operators are defined for this type of hierarchy, and theoretical results that show their usefulness are proved. Our preliminary results highlight two promising advantages of following a multigrid approach in contrast with a pure interior point method: the percentage of problems that can be solved to a high accuracy is much higher, and the time necessary to find a solution can be reduced significantly, especially for large scale problems.
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Khan, Ejaz. "Techniques itératives pour les systèmes CDMA et algorithmes de détection MIMO." Paris, ENST, 2003. http://www.theses.fr/2003ENST0020.

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Dans la première partie de cette thèse, nous utilisons l'algorithme d'Expectation-Maximization (EM) pour estimer en aveugle les amplitudes des coefficients du canal, et nous comparons les résultats avec la borne de Cramer-Rao. De plus, nous développons une version relaxe de la détection MV, à faible complexité et montrons que ses performances surpassent celles du détecteur d'erreur quadratique moyenne minimale (EQMM). La deuxième partie de cette thèse concerne le problème de la détection dans les systèmes MEMS. Nous proposerons un algorithme de détection MV utilisant une approche géométrique discrète. L'avantage de cet algorithme est sa complexité polynomiale, quel que soit le rapport signal-bruit, et le fait qu'aucune méthode heuristique n'est employé. Nous obtenons une méthode MV approches a faible complexité par l'approche de la programmation en cone du deuxième ordre. Nous établissons également des bornes sur la performance de la méthode de programmation semi-definie. Jusqu'ici, la connaissance de l'état du canal était considéré comme parfaite. Nous avons également explore le problème de la détection sans connaissance du canal au récepteur. Le résultat est un algorithme d'estimation conjointe du canal et des symboles, base sur l'algorithme EM, et la théorie du champ dynamique moyen (CDM, ou mean field theory, méthode largement utilise en physique statistique) pour en réduire la complexité L'approche du CDM est utilise pour approximer les probabilité {\em a posteriori} d'interférence d'access multiple. Les performances de la méthode propose sont compares a celles du détecteur MV exact pour un canal connu
We focus on low complexity maximum likelihood detection. The em algorithm is a broadly applicable approach to the iterative computation of ml estimates, useful in variety of incomplete-data problems, where algorithms such as the newton-raphson method may turn out to be more complicated. In the first part of the thesis, we use em algorithm to estimate the channel amplitudes blindly and compare the results with the cramer-rao bound (crb). The second part of the thesis concerns the detection problem in mimo systems. We are able to device an algorithm for approximate ml detection using a discrete geometric approach. The advantage of this algorithm is that its performance is polynomial irrespective of the snr and no heuristic is employed in our algorithm. An alternative way to ml problem is to devise low complexity algorithms whose performance is close to the exact ml. This can be done using semidefinite programming (sdp) approach. The computational complexity of the sdp approach is comparable to the average complexity of the sphere decoder but still it is quite complicated for large systems. We obtained low complexity (by reducing the number of the variables) approximate ml by second order cone programming (socp) approach. In the above discussion the channel state information is assumed to be known at the receiver. We further looked into the problem of detection with no channel knowledge at the receiver. The result was the joint channel-symbol estimation. We obtained the results of joint channel-symbol estimation using em algorithm and in order to reduce the complexity of the resulting em algorithm, we used mean field theory (mft) approach
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Passuello, Alberto. "Semidefinite programming in combinatorial optimization with applications to coding theory and geometry." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00948055.

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We apply the semidefinite programming method to obtain a new upper bound on the cardinality of codes made of subspaces of a linear vector space over a finite field. Such codes are of interest in network coding.Next, with the same method, we prove an upper bound on the cardinality of sets avoiding one distance in the Johnson space, which is essentially Schrijver semidefinite program. This bound is used to improve existing results on the measurable chromatic number of the Euclidean space.We build a new hierarchy of semidefinite programs whose optimal values give upper bounds on the independence number of a graph. This hierarchy is based on matrices arising from simplicial complexes. We show some properties that our hierarchy shares with other classical ones. As an example, we show its application to the problem of determining the independence number of Paley graphs.
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Niu, Yi Shuai. "Programmation DC et DCA en optimisation combinatoire et optimisation polynomiale via les techniques de SDP : codes et simulations numériques." Phd thesis, INSA de Rouen, 2010. http://tel.archives-ouvertes.fr/tel-00557911.

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L'objectif de cette thèse porte sur des recherches théoriques et algorithmiques d'optimisation locale et globale via les techniques de programmation DC & DCA, Séparation et Evaluation (SE) ainsi que les techniques de relaxation DC/SDP, pour résoudre plusieurs types de problèmes d'optimisation non convexe (notamment en Optimisation Combinatoire et Optimisation Polynomiale). La thèse comporte quatre parties :La première partie présente les outils fondamentaux et les techniques essentielles en programmation DC & l'Algorithme DC (DCA), ainsi que les techniques de relaxation SDP, et les méthodes de séparation et évaluation (SE).Dans la deuxième partie, nous nous intéressons à la résolution de problèmes de programmation quadratique et linéaire mixte en variables entières. Nous proposons de nouvelles approches locales et globales basées sur DCA, SE et SDP. L'implémentation de logiciel et des simulations numériques sont aussi étudiées.La troisième partie explore des approches de la programmation DC & DCA en les combinant aux techniques SE et SDP pour la résolution locale et globale de programmes polynomiaux. Le programme polynomial avec des fonctions polynomiales homogènes et son application à la gestion de portefeuille avec moments d'ordre supérieur en optimisation financière ont été discutés de manière approfondie dans cette partie.Enfin, nous étudions dans la dernière partie un programme d'optimisation sous contraintes de type matrices semi-définies via nos approches de la programmation DC. Nous nous consacrons à la résolution du problème de réalisabilité des contraintes BMI et QMI en contrôle optimal.L'ensemble de ces travaux a été implémenté avec MATLAB, C/C++ ... nous permettant de confirmer l'utilisation pratique et d'enrichir nos travaux de recherche.
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Fraticelli, Barbara M. P. "Semidefinite Cuts and Partial Convexification Techniques with Applications to Continuous Nonconvex Optimization, Stochastic Integer Programming, and Facility Layout Problems." Diss., Virginia Tech, 2001. http://hdl.handle.net/10919/27293.

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This dissertation develops efficient solution techniques for general and problem-specific applications within nonconvex optimization, exploiting the constructs of the Reformulation-Linearization Technique (RLT). We begin by developing a technique to enhance general problems in nonconvex optimization through the use of a new class of RLT cuts, called semidefinite cuts. While these cuts are valid for any general problem for which RLT is applicable, we demonstrate their effectiveness in optimizing a nonconvex quadratic objective function over a simplex. Computational results indicate that on average, the semidefinite cuts have reduced the number of nodes in the branch-and-bound tree by a factor of 37.6, while decreasing solution time by a factor of 3.4. The semidefinite cuts have also led to a significant reduction in the optimality gap at termination, in some cases producing optimal solutions for problems that could not be solved using RLT alone. We then narrow our focus to the class of mixed-integer programming (MIP) problems, and develop a modification of Bendersâ decomposition method using concepts from RLT and lift-and-project cuts. This method is particularly motivated by the class of two-stage stochastic programs with integer recourse. The key idea is to design an RLT or lift-and-project cutting plane scheme for solving the subproblems where the cuts generated have right-hand sides that are functions of the first-stage variables. An illustrative example is provided to elucidate the proposed approach. The focus is on developing a first comprehensive finitely convergent extension of Bendersâ methodology for problems having 0-1 mixed-integer subproblems. We next address a specific challenging MIP application known as the facility layout problem, and we significantly improve its formulation through outer-linearization techniques and concepts from disjunctive programming. The enhancements produce a substantial increase in the accuracy of the layout produced, while at the same time, providing a dramatic reduction in computational effort. Overall, the maximum error in department size was reduced from about 6% to nearly zero, while solution time decreased by a factor of 110. Previously unsolved test problems from the literature that had defied even approximate solution methods have been solved to exact optimality using our proposed approach.
Ph. D.
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Fletcher, Thomas P. "Optimal energy management strategy for a fuel cell hybrid electric vehicle." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/25567.

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The Energy Management Strategy (EMS) has a huge effect on the performance of any hybrid vehicle because it determines the operating point of almost every component associated with the powertrain. This means that its optimisation is an incredibly complex task which must consider a number of objectives including the fuel consumption, drive-ability, component degradation and straight-line performance. The EMS is of particular importance for Fuel Cell Hybrid Electric Vehicles (FCHEVs), not only to minimise the fuel consumption, but also to reduce the electrical stress on the fuel cell and maximise its useful lifetime. This is because the durability and cost of the fuel cell stack is one of the major obstacles preventing FCHEVs from being competitive with conventional vehicles. In this work, a novel EMS is developed, specifcally for Fuel Cell Hybrid Electric Vehicles (FCHEVs), which considers not only the fuel consumption, but also the degradation of the fuel cell in order to optimise the overall running cost of the vehicle. This work is believed to be the first of its kind to quantify effect of decisions made by the EMS on the fuel cell degradation, inclusive of multiple causes of voltage degradation. The performance of this new strategy is compared in simulation to a recent strategy from the literature designed solely to optimise the fuel consumption. It is found that the inclusion of the degradation metrics results in a 20% increase in fuel cell lifetime for only a 3.7% increase in the fuel consumption, meaning that the overall running cost is reduced by 9%. In addition to direct implementation on board a vehicle, this technique for optimising the degradation alongside the fuel consumption also allows alternative vehicle designs to be compared in an unbiased way. In order to demonstrate this, the novel optimisation technique is subsequently used to compare alternative system designs in order to identify the optimal economic sizing of the fuel cell and battery pack. It is found that the overall running cost can be minimised by using the smallest possible fuel cell stack that will satisfy the average power requirement of the duty cycle, and by using an oversized battery pack to maximise the fuel cell effciency and minimise the transient loading on the stack. This research was undertaken at Loughborough University as part of the Doctoral Training Centre (DTC) in Hydrogen, Fuel Cells and Their Applications in collaboration with the University of Birmingham and Nottingham University and with sponsorship from HORIBA-MIRA (Nuneaton, UK). A Microcab H4 test vehicle has been made available for use in testing for this research which was previously used for approximately 2 years at the University of Birmingham. The Microcab H4 is a small campus based vehicle designed for passenger transport and mail delivery at low speeds as seen on a university campus. It has a top speed of approximately 30mph, and is fitted with a 1.2kW fuel cell and a 2kWh battery pack.
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Halalchi, Houssem. "Commande linéaire à paramètres variants des robots manipulateurs flexibles." Phd thesis, Université de Strasbourg, 2012. http://tel.archives-ouvertes.fr/tel-00762367.

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Les robots flexibles sont de plus en plus utilisés dans les applications pratiques. Ces robots sont caractérisés par une conception mécanique légère, réduisant ainsi leur encombrement, leur consommation d'énergie et améliorant leur sécurité. Cependant, la présence de vibrations transitoires rend difficile un contrôle précis de la trajectoire de ces systèmes. Cette thèse est précisément consacrée à l'asservissement en position des manipulateurs flexibles dans les espaces articulaire et opérationnel. Des méthodes de commande avancées, basées sur des outils de la commande robuste et de l'optimisation convexe, ont été proposées. Ces méthodes font en particulier appel à la théorie des systèmes linéaires à paramètres variants (LPV) et aux inégalités matricielles linéaires (LMI). En comparaison avec des lois de commande non-linéaires disponibles dans la littérature, les lois de commande LPV proposées permettent de considérerdes contraintes de performance et de robustesse de manière simple et systématique. L'accent est porté dans notre travail sur la gestion appropriée de la dépendance paramétrique du modèle LPV, en particulier les dépendances polynomiale et rationnelle. Des simulations numériques effectuées dans des conditions réalistes, ont permis d'observer une meilleure robustesse de la commande LPV par rapport à la commande non-linéaire par inversion de modèle face aux bruits de mesure, aux excitations de haute fréquence et aux incertitudes de modèle.
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Monori, Akos. "Task assignment optimization in SAP Extended WarehouseManagement." Thesis, Högskolan Dalarna, Datateknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:du-3598.

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Nowadays in the world of mass consumption there is big demand for distributioncenters of bigger size. Managing such a center is a very complex and difficult taskregarding to the different processes and factors in a usual warehouse when we want tominimize the labor costs. Most of the workers’ working time is spent with travelingbetween source and destination points which cause deadheading. Even if a worker knowsthe structure of a warehouse well and because of that he or she can find the shortest pathbetween two points, it is still not guaranteed that there won’t be long traveling timebetween the locations of two consecutive tasks. We need optimal assignments betweentasks and workers.In the scientific literature Generalized Assignment Problem (GAP) is a wellknownproblem which deals with the assignment of m workers to n tasks consideringseveral constraints. The primary purpose of my thesis project was to choose a heuristics(genetic algorithm, tabu search or ant colony optimization) to be implemented into SAPExtended Warehouse Management (SAP EWM) by with task assignment will be moreeffective between tasks and resources.After system analysis I had to realize that due different constraints and businessdemands only 1:1 assingments are allowed in SAP EWM. Because of that I had to use adifferent and simpler approach – instead of the introduced heuristics – which could gainbetter assignments during the test phase in several cases. In the thesis I described indetails what ware the most important questions and problems which emerged during theplanning of my optimized assignment method.
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Gul, Sufi Tabassum. "Optimization of Multi-standards Software Defined Radio Equipments: A Common Operators Approach." Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00446230.

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La technique de paramétrisation est très prometteuse pour la conception radio logicielle. La radio logicielle consiste à concevoir des systèmes multi-standards qui tirent bénéfice des possibilités de programmation ou de reconfiguration offertes par les composants de traitement la constituant. Cette thèse étudie la technique de paramétrisation par opérateurs communs. Les opérateurs communs sont des unités de traitements communes à plusieurs opérations qu'effectue un équipement, quelle que soit la couche du modèle OSI à laquelle elles appartiennent. La méthode proposée repose sur une approche théorique afin de résoudre le problème de conception d'un équipement multi-standards. Elle consiste en une optimisation d'un hypergraphe. La conception de l'équipement est représentée par des opérateurs à différents niveaux de granularité dans un graphe acyclique orienté. Le niveau le plus élevé représente une approche de conception d'équipements multi-standards de type Velcro. Plus les opérateurs sont bas dans le graphe, plus leur coût est faible en termes de complexité, mais plus il faut faire appel de fois à eux pour effectuer des opérations de différentes sortes. Nous décrivons ensuite en tant qu'exemples des conception basées sur les opérateurs DMFFT (dual mode FFT), LFSR (linear feedback shift register) et le cas du FRMFB (frequency response masking filter bank). Les solutions basées sur les opérateurs communs proposées dans cette thèse peuvent contribuer à optimiser la conception des futurs équipements multi-standards de radio logicielle qui devront supporter de nombreux standards de communication sans fil.
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Mathews, Steffy Ann. "Optimization of an SDR Based Aerial Base Station." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1011834/.

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Most times people are unprepared to face natural disasters resulting in chaos, increased number of deaths, etc.Emergency responders need an efficiently working communication network to get in touch with the emergency services like hospitals, police, fire and rescue as well as people who are stranded. Such a network is also the need of the hour for survivors to contact their near and dear ones. One of the major barriers of communication during an emergency is the destruction of network elements. In case the communication devices survive the calamity, odds of the network getting congested are certainly high because almost everyone will be trying to use the same network resources. An important factor when dealing with emergency situations is the calls for an immediate response and an efficient Emergency Communication Systems (ECS). Currently there is a capability gap between existing ECS solutions and what we dream of achieving. Most current solutions do not meet cost or mobility constraints. An inexpensive, portable and mobile system will fulfill this capability gap. The main purpose of this research is to optimize the altitude and received signal strength of an aerial base station to provide maximum radio coverage on the ground as well as propose the best fit radio propagation channel model to carry out the experiment for the current scenario.
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Books on the topic "SDP optimization"

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SAP performance optimization guide. 6th ed. Bonn: Galileo Press, 2011.

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SAP performance optimization guide: Analyzing and tuning SAP systems. 7th ed. Bonn: Galileo Press, 2013.

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SAP R/3 performance optimization: The official SAP guide. San Francisco: Sybex, 1999.

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Christensen, Jesper. SAP BW: Administration and performance optimization. Bonn: Galileo Press, 2014.

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Corporation, International Business Machines, ed. DB2 optimization techniques for SAP database migration and Unicode conversion. [Poughkeepsie, N.Y.?]: IBM Corporation, International Technical Support Organization, 2009.

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service), SpringerLink (Online, ed. Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE. New York, NY: Springer New York, 2013.

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Neureither, A. SAP System Landscape Optimization. SAP press, 2004.

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SAP Performance Optimization Guide. SAP Press, 2002.

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Inventory Optimization with SAP. Rheinwerk Publishing Inc., 2009.

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SAP Performance Optimization Guide. 3rd ed. SAP Press, 2003.

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Book chapters on the topic "SDP optimization"

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Luo, Zhi-Quan, Jos F. Sturm, and Shuzhong Zhang. "Superlinear Convergence of a Symmetric Primal-Dual Path Following Algorithm for SDP." In Applied Optimization, 283–97. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4613-3335-7_14.

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Shamsi, Davood, Nicole Taheri, Zhisu Zhu, and Yinyu Ye. "Conditions for Correct Sensor Network Localization Using SDP Relaxation." In Discrete Geometry and Optimization, 279–301. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00200-2_16.

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Navascués, Miguel, Stefano Pironio, and Antonio Acín. "SDP Relaxations for Non-Commutative Polynomial Optimization." In Handbook on Semidefinite, Conic and Polynomial Optimization, 601–34. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0769-0_21.

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Sotirov, Renata. "SDP Relaxations for Some Combinatorial Optimization Problems." In Handbook on Semidefinite, Conic and Polynomial Optimization, 795–819. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0769-0_27.

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Lemaréchal, Claude, and François Oustry. "SDP Relaxations in Combinatorial Optimization from a Lagrangian Viewpoint." In Nonconvex Optimization and Its Applications, 119–34. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4613-0279-7_6.

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Lasserre, Jean B. "Convergent SDP-Relaxations for Polynomial Optimization with Sparsity." In Lecture Notes in Computer Science, 263–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11832225_27.

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Elbassioni, Khaled, and Kazuhisa Makino. "Oracle-Based Primal-Dual Algorithms for Packing and Covering Semidefinite Programs." In Sublinear Computation Paradigm, 47–63. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4095-7_4.

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AbstractPacking and covering semidefinite programs (SDPs) appear in natural relaxations of many combinatorial optimization problems as well as a number of other applications. Recently, several techniques have been proposed that utilize the particular structure of this class of problems in order to obtain more efficient algorithms than those offered by general SDP solvers. For certain applications, it may be necessary to deal with SDPs with a very large number of (e.g., exponentially or even infinitely many) constraints. In this chapter, we give an overview of some of the techniques that can be used to solve this class of problems, focusing on multiplicative weight updates and logarithmic-potential methods.
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Lasserre, Jean B. "An Explicit Exact SDP Relaxation for Nonlinear 0-1 Programs." In Integer Programming and Combinatorial Optimization, 293–303. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45535-3_23.

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Kim, Sunyoung, and Masakazu Kojima. "Exploiting Sparsity in SDP Relaxation of Polynomial Optimization Problems." In Handbook on Semidefinite, Conic and Polynomial Optimization, 499–531. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0769-0_18.

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Hsieh, Jun-Ting, Pravesh K. Kothari, Lucas Pesenti, and Luca Trevisan. "New SDP Roundings and Certifiable Approximation for Cubic Optimization." In Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2337–62. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2024. http://dx.doi.org/10.1137/1.9781611977912.83.

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Conference papers on the topic "SDP optimization"

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White, Jules, and Douglas C. Schmidt. "R&D challenges and emerging solutions for multicore deployment/configuration optimization." In the FSE/SDP workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1882362.1882445.

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Sanmugadas, Varakini, and Rakesh K. Kapania. "Truss Topology Optimization With Semidefinite Programming and Parametric Model Order Reduction." In ASME 2023 Aerospace Structures, Structural Dynamics, and Materials Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/ssdm2023-108410.

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Abstract The feasibility of a hybrid PMOR-SDP approach, that combines semidefinite programming (SDP) and parametric model order reduction (PMOR) was investigated. When an optimization problem comprises of a linear objective and linear matrix inequality constraints, SDP provides an efficient algorithm for arriving at a globally optimum design. This is achieved by solving a linear systems of equations that simultaneously satisfies the optimality conditions of the primal and dual problems. Weight minimization of a structure subjected to frequency or buckling constraints is amenable to this approach. It is postulated that with the right choice of basis and sufficient reduction in the size of the system matrices defining the problem, the convergence of the SDP problem can be accelerated. To test this idea, the weight minimization of a 200-bar truss, subjected to a frequency constraint, was studied here owing the relative simplicity of the problem. The MOSEK solver was used to solve the linear SDP problem. It was found that the Krylov space containing the second moment provided the best basis set. However, the expected reduction in optimization time was not achieved as this approach did not preserve the sparse nature of the stiffness and mass matrices. Future work will study structure-preserving model order reduction to address this issue.
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Lee, Soomin, and Michael M. Zavlanos. "Approximate projections for decentralized optimization with SDP constraints." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798403.

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Wu, Liangting, and Roberto Tron. "An SDP Optimization Formulation for the Inverse Kinematics Problem." In 2023 62nd IEEE Conference on Decision and Control (CDC). IEEE, 2023. http://dx.doi.org/10.1109/cdc49753.2023.10384035.

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Zhang, Qinghong, Gang Chen, and Ting Zhang. "Self-Dual Embedding for SDP Using ELSD and its Lagrangian Dual." In 2010 Third International Joint Conference on Computational Science and Optimization. IEEE, 2010. http://dx.doi.org/10.1109/cso.2010.139.

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Krechetov, Mikhail, Jakub Marecek, Yury Maximov, and Martin Takac. "Entropy-Penalized Semidefinite Programming." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/157.

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Low-rank methods for semi-definite programming (SDP) have gained a lot of interest recently, especially in machine learning applications. Their analysis often involves determinant-based or Schatten-norm penalties, which are difficult to implement in practice due to high computational efforts. In this paper, we propose Entropy-Penalized Semi-Definite Programming (EP-SDP), which provides a unified framework for a broad class of penalty functions used in practice to promote a low-rank solution. We show that EP-SDP problems admit an efficient numerical algorithm, having (almost) linear time complexity of the gradient computation; this makes it useful for many machine learning and optimization problems. We illustrate the practical efficiency of our approach on several combinatorial optimization and machine learning problems.
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Alsaleh, Ibrahim, Lingling Fan, and Minyue Ma. "Mixed-Integer SDP Relaxation-based Volt/Var Optimization for Unbalanced Distribution Systems." In 2019 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2019. http://dx.doi.org/10.1109/pesgm40551.2019.8973879.

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Tomasin, Stefano, and Tomaso Erseghe. "Constrained optimization of local sources generation in smart grids by SDP approximation." In 2011 IEEE International Symposium on Power Line Communications and Its Applications (ISPLC). IEEE, 2011. http://dx.doi.org/10.1109/isplc.2011.5764388.

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Allen-Zhu, Zeyuan, Yin Tat Lee, and Lorenzo Orecchia. "Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver." In Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2015. http://dx.doi.org/10.1137/1.9781611974331.ch127.

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Rapoport, Lev, and Timofey Tormagov. "Using of the SDP Relaxation Method for Optimization of the Satellites Set Chosen for Positioning." In 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018). Institute of Navigation, 2018. http://dx.doi.org/10.33012/2018.15994.

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Reports on the topic "SDP optimization"

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Alwan, Iktimal, Dennis D. Spencer, and Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, December 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.

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Objective: To compare the performance of popular machine learning algorithms (ML) in mapping the sensorimotor cortex (SM) and identifying the anterior lip of the central sulcus (CS). Methods: We evaluated support vector machines (SVMs), random forest (RF), decision trees (DT), single layer perceptron (SLP), and multilayer perceptron (MLP) against standard logistic regression (LR) to identify the SM cortex employing validated features from six-minute of NREM sleep icEEG data and applying standard common hyperparameters and 10-fold cross-validation. Each algorithm was tested using vetted features based on the statistical significance of classical univariate analysis (p<0.05) and extended () 17 features representing power/coherence of different frequency bands, entropy, and interelectrode-based distance. The analysis was performed before and after weight adjustment for imbalanced data (w). Results: 7 subjects and 376 contacts were included. Before optimization, ML algorithms performed comparably employing conventional features (median CS accuracy: 0.89, IQR [0.88-0.9]). After optimization, neural networks outperformed others in means of accuracy (MLP: 0.86), the area under the curve (AUC) (SLPw, MLPw, MLP: 0.91), recall (SLPw: 0.82, MLPw: 0.81), precision (SLPw: 0.84), and F1-scores (SLPw: 0.82). SVM achieved the best specificity performance. Extending the number of features and adjusting the weights improved recall, precision, and F1-scores by 48.27%, 27.15%, and 39.15%, respectively, with gains or no significant losses in specificity and AUC across CS and Function (correlation r=0.71 between the two clinical scenarios in all performance metrics, p<0.001). Interpretation: Computational passive sensorimotor mapping is feasible and reliable. Feature extension and weight adjustments improve the performance and counterbalance the accuracy paradox. Optimized neural networks outperform other ML algorithms even in binary classification tasks. The best-performing models and the MATLAB® routine employed in signal processing are available to the public at (Link 1).
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Oblow, E. M. STP: A Stochastic Tunneling Algorithm for Global Optimization. Office of Scientific and Technical Information (OSTI), May 1999. http://dx.doi.org/10.2172/814395.

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Oron, Gideon, Raphi Mandelbaum, Carlos E. Enriquez, Robert Armon, Yoseph Manor, L. Gillerman, A. Alum, and Charles P. Gerba. Optimization of Secondary Wastewater Reuse to Minimize Environmental Risks. United States Department of Agriculture, December 1999. http://dx.doi.org/10.32747/1999.7573077.bard.

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The main purpose of the research was to examine approaches and to evaluate methods for minimizing the risks during applying treated domestic wastewater for agricultural irrigation. This general purpose consisted of examining under field conditions the possibilities when implementing different application technologies for minimizing health and environmental risks. It was assumed that Subsurface Drip Irrigation (SDI) will provide adequate conditions for safe effluent reuse. Controlled field experiments where conducted in commercial fields to evaluate the alternatives. Main efforts where conducted in Israel in the grape vineyard in Arad heights, in the field crops in Kibbutz Chafets Chaim and in Arizona in fields adjacent to the University campus. The complementary part was to examine the behavior of the various pathogens in the effluent-soil-plant system. The analysis is based on controlled experiments, primarily in greenhouse along with field experiments. Molecular biology methods were used to identify the behavior of the pathogens in the components of the system. The project included as well examining the effluent quality in various sites, primarily those in which treated wastewater is reused for agricultural irrigation. The monitoring included conventional parameters however, also parasites such as Giardia and Cryptosporidium. The results obtained indicate the prominent advantages of using Subsurface Drip Irrigation (SDI) method for minimizing health and environmental risks during application of secondary effluent. A theoretical model for assessing the risks while applying treated wastewater was completed as well. The management model shows the risks during various scenarios of wastewater quality, application technology and related human exposure.
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King, Wayne. Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, May 2023. http://dx.doi.org/10.4271/epr2023011.

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<div class="section abstract"><div class="htmlview paragraph">Success in metal additive manufacturing (AM) relies on the optimization of a large set of process parameters to achieve materials whose properties and performance meet design and safety requirements. Despite continuous improvements in the process over the years, the quality of AM parts remains a major concern for manufacturers. Today, researchers are starting to move from discrete geometry-dependent build parameters to continuously variable or dynamically changing parameters that are geometry- and scan-path aware. This approach has become known as “feedforward control.”</div><div class="htmlview paragraph"><b>Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing</b> discusses the origins of feedforward control, its early implementations in AM, the current state of the art, and a path forward to its broader adoption.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
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Kolodziejczyk, Bart. Emergence of Quantum Computing Technologies in Automotive Applications: Opportunities and Future Use Cases. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, April 2024. http://dx.doi.org/10.4271/epr2024008.

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<div class="section abstract"><div class="htmlview paragraph">Quantum computing and its applications are emerging rapidly, driving excitement and extensive interest across all industry sectors, from finance to pharmaceuticals. The automotive industry is no different. Quantum computing can bring significant advantages to the way we commute, whether through the development of new materials and catalysts using quantum chemistry or improved route optimization. Quantum computing may be as important as the invention of driverless vehicles.</div><div class="htmlview paragraph"><b>Emergence of Quantum Computing Technologies in Automotive Applications: Opportunities and Future Use Cases</b> attempts to explain quantum technology and its various advantages for the automotive industry. While many of the applications presented are still nascent, they may become mainstream in a decade or so.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
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Bleuel, D. L., and R. J. Donahue. Optimization of the {sup 7}Li(p,n) proton beam energy for BNCT applications. Office of Scientific and Technical Information (OSTI), February 1996. http://dx.doi.org/10.2172/212700.

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Bleuel, B. L., and R. J. Donahue. Optimization of the {sup 7}Li(p,n) proton beam energy for BNCT applications. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/273022.

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Heinkenschloss, Matthias, Denis Ridzal, and Miguel Antonio Aguilo. Numerical study of a matrix-free trust-region SQP method for equality constrained optimization. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1038211.

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Khan, Samir. Towards MRO 4.0: Challenges for Digitalization and Mapping Emerging Technologies. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, April 2023. http://dx.doi.org/10.4271/epr2023007.

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<div class="section abstract"><div class="htmlview paragraph">With technological breakthroughs in electric land vehicles revolutionizing their respective industry, maintenance, repair, and overhaul (MRO) facilities in aviation are also adopting digital technologies in their practices. But despite this drive towards digitalization, the industry is still dominated by manual labor and subjective assessments. Today, several technologies, processes, and practices are being championed to resolve some of these outstanding challenges. Considering this, it is important to present current perspectives regarding where the technology stands today and how we can evaluate capabilities for autonomous decision support systems that prescribe maintenance activities. Overlooking some of these unsettled domain issues can potentially undermine any benefits in speed, process, and resilience promised by such systems.</div><div class="htmlview paragraph"><b>Towards MRO 4.0: Challenges for Digitalization and Mapping Emerging Technologies</b> provides some understanding of specific motivating factors by focusing on the digitalization challenges for MRO 4.0 and the role of building “trust” in technology by reimagining stakeholder experiences. It examines overarching issues, such as data management, robotics, optimization, artificial intelligence, and systems engineering.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
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Weller, Joel I., Ignacy Misztal, and Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, March 2015. http://dx.doi.org/10.32747/2015.7594404.bard.

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The main objectives of this research was to detect the specific polymorphisms responsible for observed quantitative trait loci and develop optimal strategies for genomic evaluations and selection for moderate (Israel) and large (US) dairy cattle populations. A joint evaluation using all phenotypic, pedigree, and genomic data is the optimal strategy. The specific objectives were: 1) to apply strategies for determination of the causative polymorphisms based on the “a posteriori granddaughter design” (APGD), 2) to develop methods to derive unbiased estimates of gene effects derived from SNP chips analyses, 3) to derive optimal single-stage methods to estimate breeding values of animals based on marker, phenotypic and pedigree data, 4) to extend these methods to multi-trait genetic evaluations and 5) to evaluate the results of long-term genomic selection, as compared to traditional selection. Nearly all of these objectives were met. The major achievements were: The APGD and the modified granddaughter designs were applied to the US Holstein population, and regions harboring segregating quantitative trait loci (QTL) were identified for all economic traits of interest. The APGD was able to find segregating QTL for all the economic traits analyzed, and confidence intervals for QTL location ranged from ~5 to 35 million base pairs. Genomic estimated breeding values (GEBV) for milk production traits in the Israeli Holstein population were computed by the single-step method and compared to results for the two-step method. The single-step method was extended to derive GEBV for multi-parity evaluation. Long-term analysis of genomic selection demonstrated that inclusion of pedigree data from previous generations may result in less accurate GEBV. Major conclusions are: Predictions using single-step genomic best linear unbiased prediction (GBLUP) were the least biased, and that method appears to be the best tool for genomic evaluation of a small population, as it automatically accounts for parental index and allows for inclusion of female genomic information without additional steps. None of the methods applied to the Israeli Holstein population were able to derive GEBV for young bulls that were significantly better than parent averages. Thus we confirm previous studies that the main limiting factor for the accuracy of GEBV is the number of bulls with genotypes and progeny tests. Although 36 of the grandsires included in the APGD were genotyped for the BovineHDBeadChip, which includes 777,000 SNPs, we were not able to determine the causative polymorphism for any of the detected QTL. The number of valid unique markers on the BovineHDBeadChip is not sufficient for a reasonable probability to find the causative polymorphisms. Complete resequencing of the genome of approximately 50 bulls will be required, but this could not be accomplished within the framework of the current project due to funding constraints. Inclusion of pedigree data from older generations in the derivation of GEBV may result is less accurate evaluations.
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