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arXiv 2024年

作者： Newey, Joshua Whitehead, Jared P. Carlson, Elizabeth

We review an algorithm developed for parameter estimation within the Continuous Data Assimilation (CDA) approach. We present an alternative derivation for the algorithm presented in a paper by Carlson, Hudson, and Larios (CHL) [21]. This derivation relies on the same assumptions as the previous derivation but frames the problem as a finite dimensional root-finding problem. Within the approach we develop, the algorithm developed in [21] is simply a realization of Newton’s method. We then consider implementing other derivative based optimization algorithms;we show that the Levenberg Maqrquardt algorithm has similar performance to the CHL algorithm in the single parameter estimation case and generalizes much better to fitting multiple parameters. We then implement these methods in three example systems: the Lorenz’63 model, the two-layer Lorenz’96 model, and the Kuramoto-Sivashinsky equation. © 2024, CC BY.

关键词： optimization algorithms

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A∗ for Graphs of Convex Sets

arXiv

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arXiv 2024年

作者： Sundar, Kaarthik Rathinam, Sivakumar Los Alamos Research Laboratory NM88220 United States Texas A&M University College StationTX77843 United States

We present a novel algorithm that fuses the existing convex-programming based approach with heuristic information to find optimality guarantees and near-optimal paths for the Shortest Path Problem in the Graph of Convex Sets (SPPGCS). Our method, inspired by A∗, initiates a best-first-like procedure from a designated subset of vertices and iteratively expands it until further growth is neither possible nor beneficial. Traditionally, obtaining solutions with bounds for an optimization problem involves solving a relaxation, modifying the relaxed solution to a feasible one, and then comparing the two solutions to establish bounds. However, for SPP-GCS, we demonstrate that reversing this process can be more advantageous, especially with Euclidean travel costs. In other words, we initially employ A∗ to find a feasible solution for SPP-GCS, then solve a convex relaxation restricted to the vertices explored by A∗ to obtain a relaxed solution, and finally, compare the solutions to derive bounds. We present numerical results to highlight the advantages of our algorithm over the existing approach in terms of the sizes of the convex programs solved and computation time. Copyright © 2024, The Authors. All rights reserved.

关键词： optimization algorithms

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Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems

arXiv

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arXiv 2024年

作者： Savchuk, O.S. Alkousa, M.S. Shushko, A.S. Vyguzov, A.A. Stonyakin, F.S. Pasechnyuk, D.A. Gasnikov, A.V. V. I. Vernadsky Crimean Federal University Vernadsky Avenue 4 Simferopol Russia Adyghe State University 208 Pervomayskaya st. Maykop Russia Innopolis University Universitetskaya Str. 1 Innopolis420500 Russia Moscow Institute of Physics and Technology 9 Institutsky lane Dolgoprudny141701 Russia Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates Ivannikov Institute for System Programming The Russian Academy of Sciences Russia

In this paper, we propose some accelerated methods for solving optimization problems under the condition of relatively smooth and relatively Lipschitz continuous functions with an inexact oracle. We consider the problem of minimizing the convex differentiable and relatively smooth function concerning a reference convex function. The first proposed method is based on a similar triangles method with an inexact oracle, which uses a special triangular scaling property for the used Bregman divergence. The other proposed methods are non-adaptive and adaptive (tuning to the relative smoothness parameter) accelerated Bregman proximal gradient methods with an inexact oracle. These methods are universal in the sense that they are applicable not only to relatively smooth but also to relatively Lipschitz continuous optimization problems. We also introduced an adaptive intermediate Bregman method which interpolates between slower but more robust algorithms non-accelerated and faster, but less robust accelerated algorithms. We conclude the paper with the results of numerical experiments demonstrating the advantages of the proposed algorithms for the Poisson inverse problem. © 2024, CC BY.

关键词： optimization algorithms

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Model predictive PWM of a single phase inverter: A nonlinear transformation approach

Model predictive PWM of a single phase inverter: A nonlinear...

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IEEE Energy Conversion Congress and Exposition

作者： S. Aimer Corp. Res. ABB Baden-Dattwil Switzerland

ISBN: (纸本)9781467371520

The paper considers optimal pulse-width modulation of a single phase voltage source inverter with LC filter. The approach is based on model predictive control which requires a non-convex optimization problem to be solved in real-time. A new optimization algorithm for solving the problem is presented. The proposed algorithm utilizes an invariance property of the LC filter to recast the non-convex optimization problem as a convex quadratic problem. The novel algorithm has significant advantages compared to previously applied methods since it has lower complexity and is, under certain assumptions, guaranteed to find the global optimum.

关键词： single-phase inverter optimization algorithms voltage source inverter LC FILTERS single phase global optimum Non-Convex Pulse width modulation

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Design of Constellation Sets for Multistage Systems

Design of Constellation Sets for Multistage Systems

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IEEE Global Communications Conference

作者： Guido Montorsi Politecnico di Torino Dipartimento di Elettronica e Telecomunicazioni

ISBN: (纸本)9781509013296

We consider the problem of designing constellation sets for multistage systems for high spectral efficiencies. In particular we will focus on two-stage systems where the cascaded decoding stages are associated to three types of receivers with different complexities and performances. The optimal receiver (S) processes the symbol LLR and delivers the maximum possible throughput, the simpler BICM receiver (B) processes in parallel bit LLR derived from the observation, and finally the simplest hard receiver (H) takes an ML hard decision on the observation and processes the sequence of estimated bits with algebraic-like decoders. Optimal constellation sets achieving the maximum possible mutual information depend on the target receiver structure and thus requires separate optimization. Using a variation of the optimization algorithm based on simulated annealing previously introduced we provide optimal constellation sets with 16 to 256 point for four variants of the two-stage receiver offering different trade-offs between complexity and performance. We will show that BH receivers, where the first stage uses a BICM approach and the second stage the even simpler hard decision receiver can provide performances within 0.2 bits from the theoretical Shannon limit in a proper range of Signal to Noise Ratio (SNR) if optimal constellation sets are used.

关键词： Receivers CONSTELLATIONS constellation design optimization algorithms SETTING Shannon limit hard-decision decoding signal to noise ratios MULTISTAGE correlators

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A Distributed Anytime Algorithm for Maximizing Occupant Comfort

A Distributed Anytime Algorithm for Maximizing Occupant Comf...

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American Control Conference

作者： Arvind U. Raghunathan Sudha Krishnamurthy Mitsubishi Electric Research Labs. United Technologies Research Center

ISBN: (纸本)9781457710957

We propose a distributed, anytime optimization algorithm to maximize the thermal comfort of building occupants. We consider the building as a set of areas consisting of zones, which are coupled by the capacity of the HVAC equipment as well as the energy and mass balance relations that govern the building dynamics. The resulting non-convex, large-dimensional, constrained optimization formulation is decomposed into area-level subproblems that are solved by distributed agents. At each timestep, the agents cooperate to converge to an equilibrium solution that determines the optimal values of the building operational variables, such as temperature and rate of air flow, that maximizes the total comfort. Our experimental results show that the distributed algorithm (i) is more scalable than the centralized optimization algorithm;(ii) produces a locally optimal solution that is comparable to that resulting from the centralized approach;and (iii) yields a feasible solution even if pre-empted before equilibrium is attained.

关键词： air flow Buildings hvac equipment COMFORT optimal solution distributed algorithms Distribute optimization algorithms THERMAL COMFORT Agents

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Optimisation algorithms for microarray biclustering

Optimisation algorithms for microarray biclustering

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Dimitri Perrin Christophe Duhamel Laboratory for Systems Biology RIKEN Center for Developmental Biology Kobe Japan and with the

ISBN: (纸本)9781457702150

In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic algorithms. We also introduce a new heuristic "Propagate", which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme, optimal or near-optimal solutions can be identified.

关键词： Microarray optimization algorithms SEARCHING ALGORITHM Genes Genetic Algorithm (GA) Propagating Dataset Ganglia Insight Bipartite graph

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Design Automation of Valve Gate Locations and Open Timing for Injection Molding of an Automotive Instrument Panel

Design Automation of Valve Gate Locations and Open Timing fo...

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IEEE International Conference on Automation Science and Engineering

作者： C.-H. Park B.-G. Pyo D.-H. Choi PIDOTECH Inc. VMTech Co. Ltd. Department of Mechanical Engineering Hanyang University

ISBN: (纸本)9781467304290

Valve gate locations and open timing for injection molding of an automotive instrument panel is to be determined to minimize the cavity pressure. To achieve design automation for obtaining the solution of this design problem, we first integrated MAPS-3D, a commercial injection molding analysis tool, to PIAnO, a commercial process integration and design optimization (PIDO) tool, using the file parsing technique. Then, we automated an iterative analysis and design procedure using a batch run capability provided by PIAnO. To obtain the optimal design solution, we employed a metamodel-based design optimization method combining an experimental design, a metamodel and an optimization algorithm available in PIAnO. Using the proposed design automation approach, the cavity pressure was found to decrease by 34.2% compared to the initial one, which clearly shows the validity of the proposed approach.

关键词： Computer-Aided Design Injection molding Instrument panels Optimal design VALVE GATE design problems PIANO CAVITY PRESSURE automotive engineering cavity design process optimization algorithms gates

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A core-set approach for distributed quadratic programming in big-data classification

A core-set approach for distributed quadratic programming in...

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IEEE Annual Conference on Decision and Control

作者： Giuseppe Notarstefano Department of Engineering Universita del Salento via Monteroni 73100 Lecce Italy

ISBN: (纸本)9781479978878

A new challenge for learning algorithms in cyberphysical network systems is the distributed solution of big-data classification problems, i.e., problems in which both the number of training samples and their dimension is high. Motivated by several problem set-ups in Machine Learning, in this paper we consider a special class of quadratic optimization problems involving a "large" number of input data, whose dimension is "big". To solve these quadratic optimization problems over peer-to-peer networks, we propose an asynchronous, distributed algorithm that scales with both the number and the dimension of the input data (training samples in the classification problem). The proposed distributed optimization algorithm relies on the notion of "core-set" which is used in geometric optimization to approximate the value function associated to a given set of points with a smaller subset of points. By computing local core-sets on a smaller version of the global problem and exchanging them with neighbors, the nodes reach consensus on a set of active constraints representing an approximate solution for the global quadratic program.

关键词： dimensions Set of points incoming data data classification active constraint quadratic programming distributed algorithms Quadratic Peer-to-peer network Distribute learning algorithms optimization algorithms

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Synthesis of Sparse Planar Array using Modified Bayesian optimization Algorithm

Synthesis of Sparse Planar Array using Modified Bayesian Opt...

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Electromagnetic Metrology Symposium

作者： B. V. Ha R. E. Zich M. Mussetta P. Pirinoli Dipartimento di Energia Politecnico di Milano Dipartimento di Elettronica Politecnico di Torino

ISBN: (纸本)9781467357067

Controlling the position of elements in sparse planar array would be the hardest work in the synthesis procedure since the array has to satisfy multiple design constraints e.g. number of elements, elements spacing and arrays aperture. In this paper, a simple method is implemented to effectively control 2-D sparse array. The approach implements two sets of data to separately manage the x- and y-coordinate of each element in the array. The array is then synthesized as an optimization problem using the recently improved version of Bayesian optimization Algorithm. As a proof of concept, the results of a 108 element sparse planar array are here presented and discussed.

关键词： Planar antennas Elements y-coordinate optimization algorithms arrays synthesis design constraints Dataset Bayesian inference

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