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IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)

作者： Ruvio, Alessandro Sapienza Univ Rome DIAEE Rome Italy

ISBN: (纸本)9798350387032;9798350387025

The paper carried out a methodology to design stationary energy storage system (ESS) employing a deterministic algorithm. The primary scope is to maximizing economic benefits arriving to define an optimal siting and sizing of the ESS utilizing deterministic algorithm. The objective function of the algorithm is set on the net present value (NPV) calculation. Numerical simulation of a d.c. railway line with new high-speed trains has been presented to assess power flow between trains, leading to the identification of suitable locations and sizes for electrical substations and storage systems within the railway network. The main scope of the proposed approach lies in using an optimization algorithm to maximize the economic advantage of installing an energy storage system in a railway line also minimizing the energy purchase from the grid with low computational effort, versatility and easy implementation features. The methodology proposed has been applied to a case study.

关键词： Optimization deterministic algorithm stationary energy storage system Railway energy saving

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deterministic algorithm and Faster algorithm for Submodular Maximization subject to a Matroid Constraint 65

Deterministic Algorithm and Faster Algorithm for Submodular ...

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65th Symposium on Foundations of Computer Science

作者： Buchbinder, Niv Feldman, Moran Tel Aviv Univ Dept Stat & Operat Res Tel Aviv Israel Univ Haifa Dept Comp Sci Haifa Israel

ISBN: (纸本)9798331516758;9798331516741

We study the problem of maximizing a monotone submodular function subject to a matroid constraint, and present for it a deterministic non-oblivious local search algorithm that has an approximation guarantee of 1 - 1/e - epsilon (for any epsilon > 0) and query complexity of (O) over tilde (epsilon)(nr), where n is the size of the ground set and r is the rank of the matroid. Our algorithm vastly improves over the previous state-of-the-art 0.5008-approximation deterministic algorithm, and in fact, shows that there is no separation between the approximation guarantees that can be obtained by deterministic and randomized algorithms for the problem considered. The query complexity of our algorithm can be improved to (O) over tilde (epsilon)(n + r root n) using randomization, which is nearly-linear for r = O(root n), and is always at least as good as the previous state-of-the-art algorithms.

关键词： submodular maximization matroid constraint deterministic algorithm fast algorithm

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deterministic algorithm for Cloud Outsourced Data

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SN Computer Science 2022年第3期3卷 223页

作者： Tajammul, Mohd Parveen, Rafat Asif, Sumaira School of Computer Science and Information Technology Jain Deemed To Be University Bangalore India Department of Computer Science Jamia Hamdard University New Delhi India

Cloud storage suffers from security. It is more prone to security breaches due to multitenant architecture and data remanence. Cloud storage is robust as well as promising platform from economic point of view as no extra cost for purchasing hardware is required. Security breaches hamper the market of cloud. Instead of attracting the mind of customers, it creates a picture of dilemma in their minds whether to cloudify or not. Many algorithms have already been designed and implemented to make cloud storage robust and secure place to outsource data but the attacks of twenty-first century uncover that they are inadequate to provide all round security to it. This research paper proposed an algorithm which determines whether the data being uploaded on cloud are sensitive or normal data. On testing data sensitivity, algorithm decides whether to upload it on public cloud or on private cloud. Moreover, if data are found to be sensitive, it is bifurcated and uploaded on private cloud after encryption with two different algorithms, else it is uploaded on public cloud. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Cloud security Cloud storage Data bifurcation deterministic algorithm Sensitive data

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An Enumeration-Based deterministic algorithm for Solving optimization Problem 6

An Enumeration-Based Deterministic Algorithm for Solving opt...

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6th IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2023

作者： Yang, Changlin Aeronautics Computing Technology Research Institute Process Management Office Xi'an China

ISBN: (纸本)9798350305623

An enumeration-based deterministic algorithm is proposed for solving optimization problem. Discretization of the feasible region for each decision variable is applied to establish search tree so that all the solutions could be enumerated. A new search region is established from the optimization of previous literation. Meanwhile, adjustment of search step with exponential decay function is conducive to reducing the search scope until the convergence of result is realized. The proposed algorithm is applied for three kinds of typical optimization problem, including Non-linear Programing Problem, Job-Shop Scheduling Problem and Traveling Salesman Problem. The results obtained by the new algorithm are compared with results of swarm intelligent optimization algorithm. Results indicate that for the combinational optimization, high convergence rate could be realized by adjusting the feasible region for each decision variable. For non-linear programming problem, the accuracy of results obtained from deterministic algorithm is better than that from self-organizing migrating algorithm, which infers that enumeration-based deterministic algorithm could be used to solve NP hard problem. © 2023 IEEE.

关键词： deterministic algorithm enumeration job-shop scheduling problem nonlinear programming problem optimization traveling salesman problem

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Efficient deterministic algorithm for Huge-Sized Noisy Sensor Localization Problems via Canonical Duality Theory

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IEEE TRANSACTIONS ON CYBERNETICS 2021年第10期51卷 5069-5081页

作者： Latorre, Vittorio Gao, David Yang Federat Univ Australia Fac Sci & Technol Ballarat Vic 3353 Australia

This paper presents a new deterministic method and a polynomial-time algorithm for solving general huge-sized sensor network localization problems. The problem is first formulated as a nonconvex minimization, which was considered as an NP-hard based on conventional theories. However, by the canonical duality theory, this challenging problem can be equivalently converted into a convex dual problem. By introducing a new optimality measure, a powerful canonical primal-dual interior (CPDI) point algorithm is developed which can solve efficiently huge-sized problems with hundreds of thousands of sensors. The new method is compared with the popular methods in the literature. Results show that the CPDI algorithm is not only faster than the benchmarks but also much more accurate on networks affected by noise on the distances.

关键词： Optimization Noise measurement Indexes Minimization Monitoring Global Positioning System Measurement uncertainty Canonical duality theory deterministic algorithm global optimization sensor network localization (SNL) problem

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An accelerated deterministic algorithm for maximizing monotone submodular minus modular function with cardinality constraint

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THEORETICAL COMPUTER SCIENCE 2024年 1016卷

作者： Gong, Shufang Liu, Bin Fang, Qizhi Ocean Univ China Sch Math Sci Qingdao 266100 Shandong Peoples R China

Submodular optimization not only covers some classical combinatorial optimization problems, but also has a wide range of applications in fields such as machine learning and artificial intelligence. For submodular maximization problems with constraints, some work has been done including the design of approximation algorithms, the measurement of approximation algorithms in terms of quality and efficiency, etc. In this paper, we consider the problem of maximizing a non-negative monotone submodular function minus a non-negative modular function with the cardinality constraint. This model has been applied to many scenarios, such as team formation problem, influence maximization problem, recommender systems problem, etc. We propose a threshold algorithm that achieve a (1/2 -..(..), 2)- bicriteria approximation ratio and query complexity..(.. log..). Our algorithm makes a small sacrifice in the approximation ratio but improves the best query complexity result of existing deterministic algorithms from..(..2) to..(.. log..) in the worst case.

关键词： Submodular minus modular Cardinality constraint Accelerated algorithm deterministic algorithm

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SpartaPlex: A deterministic algorithm with linear scalability for massively parallel global optimization of very large-scale problems

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ADVANCES IN ENGINEERING SOFTWARE 2022年第0期166卷 103090-103090页

作者： Albert, Benjamin Alexander Zhang, Arden Qiyu Johns Hopkins Univ Dept Biomed Engn Dept Comp Sci Baltimore MD 21218 USA Univ Maryland Dept Comp Sci Dept Math College Pk MD USA

SpartaPlex is a novel black-box optimization algorithm that yields superior results to state-of-the-art optimizers under tight function evaluation budgets. SpartaPlex is compared with 11 state-of-the-art optimization algorithms on 24 n-dimensional and 6 application-based benchmark problems including mechanical, structural, and antenna design optimization. Using identical computing resources, SpartaPlex finds superior objective function solutions and, as dimensionality increases, executes at least an order of magnitude faster than prior state-of-the-art. SpartaPlex is additionally evaluated for scalability using a compute cluster with 46,080 cores across 16 Graphical Processing Units. Tested in up to 100,000 dimensions, SpartaPlex demonstrates linear scalability in time with respect to dimensionality and computational resources.

关键词： Black-box optimization deterministic algorithm Global optimization Gpu clusters Large-scale optimization Linear scaling High-performance Computing Parallel scalability

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deterministic approximation algorithm for submodular maximization subject to a matroid constraint

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INTERNATIONAL JOURNAL OF CARDIOLOGY 2021年 343卷 1-15页

作者： Sun, Xin Xu, Dachuan Guo, Longkun Li, Min Beijing Univ Technol Dept Operat Res & Informat Engn Beijing 100124 Peoples R China Qilu Univ Technol Shandong Comp Sci Ctr Sch Comp Sci & Technol Shandong Key Lab Comp NetworksShandong Acad Sci Jinan 250353 Peoples R China Fuzhou Univ Sch Comp & Data Sci Fuzhou 350116 Peoples R China Shandong Normal Univ Sch Math & Stat Jinan 250014 Peoples R China

In this paper, we study the generalized submodular maximization problem with a nonnegative monotone submodular set function as the objective function and subject to a matroid constraint. The problem is generalized through the curvature parameter alpha is an element of [0, 1] which measures how far a set function deviates from linearity to submodularity. We propose a deterministic approximation algorithm which uses the approximation algorithm proposed by Buchbinder et al. [2] as a building block and inherits the approximation guarantee for alpha = 1. For general value of the curvature parameter alpha is an element of [0, 1], we present an approximation algorithm with a factor of 1+h(alpha)(y)+Delta.[3+alpha-(2+alpha)y-(1+alpha)h(alpha)(y)]/2+alpha+(1+alpha)(1-y), where y is an element of [0, 1] is a predefined parameter for tuning the ratio. In particular, when alpha = 1 we obtain a ratio 0.5008 when setting y = 0.9, coinciding with the renowned state-of-art approximate ratio; when alpha = 0 that the object is a linear function, the approximation factor equals one and our algorithm is indeed an exact algorithm that always produces optimum solutions. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Approximation algorithm Submodular maximization Total curvature Matroid constraint deterministic algorithm ADAPTIVE COMPLEXITY SET OPTIMIZATION

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Asynchronous approach in the plane: a deterministic polynomial algorithm

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DISTRIBUTED COMPUTING 2019年第4期32卷 317-337页

作者： Bouchard, Sebastien Bournat, Marjorie Dieudonne, Yoann Dubois, Swan Petit, Franck Sorbonne Univ CNRS INRIA LIP6 F-75005 Paris France Univ Picardie Jules Verne MIS Lab Amiens France

In this paper we study the task of approach of two mobile agents having the same limited range of vision and moving asynchronously in the plane. This task consists in getting them in finite time within each other's range of vision. The agents execute the same deterministic algorithm and are assumed to have a compass showing the cardinal directions as well as a unit measure. On the other hand, they do not share any global coordinates system (like GPS), cannot communicate and have distinct labels. Each agent knows its label but does not know the label of the other agent or the initial position of the other agent relative to its own. The route of an agent is a sequence of segments that are subsequently traversed in order to achieve approach. For each agent, the computation of its route depends only on its algorithm and its label. An adversary chooses the initial positions of both agents in the plane and controls the way each of them moves along every segment of the routes, in particular by arbitrarily varying the speeds of the agents. Roughly speaking, the goal of the adversary is to prevent the agents from solving the task, or at least to ensure that the agents have covered as much distance as possible before seeing each other. A deterministic approach algorithm is a deterministic algorithm that always allows two agents with any distinct labels to solve the task of approach regardless of the choices and the behavior of the adversary. The cost of a complete execution of an approach algorithm is the length of both parts of route travelled by the agents until approach is completed. Let Delta and l be the initial distance separating the agents and the length of (the binary representation of) the shortest label, respectively. Assuming that Delta andlare unknown to both agents, does there exist a deterministic approach algorithm always working at a cost that is polynomial in Delta andl? Actually the problem of approach in the plane reduces to the network problem of rendezvo

关键词： Mobile agents Asynchronous rendezvous Plane Infinite grid deterministic algorithm Polynomial cost

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Ultra high speed deterministic algorithm for transmission lines disturbance identification based on principal component analysis and Euclidean norm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年第0期80卷 312-324页

作者： Morales, J. A. Orduna, E. Rehtanz, C. Cabral, R. J. Bretas, A. S. Univ Nacl San Juan Inst Energia Elect Av Lib Gral San Martin Oeste 1109 J5400ARL San Juan Argentina Univ Politecn Salesiana Carrera Ingn Mecatron Calle Vieja 12-30 & Elia Liut Cuenca 010150 Ecuador TU Dortmund Univ Inst Energy Syst Energy Efficiency & Energy Econ Emil Figge Str 70 D-44227 Dortmund Germany Univ Fed Rio Grande do Sul Dept Elect Engn Av Osvaldo Aranha103 Room 116 BR-90035190 Porto Alegre RS Brazil

Protection devices are designed to provide high sensitivity to transients produced by undesirable conditions like lightning stroke, avoiding their operation under all tolerable events like switching operations. The problem of incorrect operation due to transient phenomena can be handled by two means, one is to allow the transients and provide additional logics in the relay, other means is to damp the oscillation from source side. Protection relays' not always must trip or send a trip signal and sometimes, only an alarm is necessary. In this context, this research presents a fast and reliable formulation for transmission lines (TLs) switching operations and lightning strokes detection and identification. The proposed methodology is based on Principal Component Analysis (PCA) and Euclidean Norm (EN);by using PCA it is possible to determine that normal operation signals describe a very well defined Ellipsoidal Pattern (EP). In this manner, by calculating the Euclidean Norm (EN) among Principal Components (PCs) for each sample and the origin of the reference Ellipsoidal Pattern, switching operations and lightning strokes are detected and identified. Test results show that the proposed algorithm presents high success on phenomena detection and identification, presenting a high potential for online applications. (c) 2016 Elsevier Ltd. All rights reserved.

关键词： deterministic algorithm Undesirable conditions Ellipsoidal pattern Euclidean norm

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