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Penalty Removal Search Algorithm for distributed Optimization of Nonconvex Functions in Economic Dispatch

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年

作者： Ge, Yiyang Wang, Zhanshan Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China State Key Lab Synthet Automation Proc Ind Shenyang 110819 Peoples R China

Nonconvexity is a usually overlooked factor in economic dispatch (ED). Enhancing the nonconvexity of the objective function leads traditional convex optimization algorithms easily to fall into the local optimum. To address the above problem, a penalty removal search algorithm (PRSA) is proposed for ED nonconvex optimization. It is composed of two distributed optimization algorithms embedded in a reinforcement learning framework. In Phase I of PRSA, a distributed optimization algorithm with projection operators is designed. It uses fewer variables to locate the region where the optimal solution belongs by the cooperative Q-learning. In Phase II of PRSA, the sigmoid function serves as a penalty function to form the second distributed optimization algorithm. This is used to skip the searched solutions and allow the algorithm to continue searching for more feasible solutions. The PRSA solves the problem that the algorithm misses feasible solutions when the nonconvex coefficients increase. Finally, the effectiveness of the PRSA is verified by numerical examples.

关键词： Linear programming Economics distributed algorithms Cost function Q-learning Germanium Costs Valves Fuels Convex functions Collaborative Q-learning (CQL) algorithm distributed optimization economic dispatch (ED) nonconvex optimization penalty removal search algorithm (PRSA)

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distributed Shortest Link Scheduling algorithms With Constant Time Complexity in IoT Under Rayleigh Fading

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IEEE ACCESS 2020年 8卷 103245-103255页

作者： Yu, Kan Yu, Jiguo Dong, Anming Li, Guangshun Qufu Normal Univ Sch Informat Sci & Engn Rizhao 276826 Peoples R China Shandong Comp Sci Ctr Natl Supercomp Ctr Jinan Jinan 250353 Peoples R China Qilu Univ Technol Shandong Acad Sci Sch Comp Sci & Technol Jinan 250353 Peoples R China

For the shortest link scheduling (SLS), i.e., scheduling a given set of links with minimum time slots, we consider the distributed algorithm design by using the locality of the protocol model with high fidelity under the Rayleigh fading. Different from most previous works, focusing on distributed algorithm design under the deterministic SINR model, which ignores the fading effects in signal propagation, we first show that a successful link of protocol model is also feasible under the deterministic SINR model, then it can be scheduled successfully with high probability under the Rayleigh fading, by upper-bounding interference outside interference range of protocol model. Then on the basis of this key conclusion, we design LLS-SLS algorithm to solve SLS within . Specifically, is the number of a sender & x2019;s neighbors within some certain range, and can be upper-bounded. Next, based on the concept of random contention, we design CLLS algorithm to schedule all links after costing time slots. In addition, extensive simulations evaluate the performance of two proposed algorithms.

关键词： Shortest link scheduling Rayleigh fading locality distributed algorithms

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A frame of reference for the performance evaluation of asynchronous, distributed decision-making algorithms

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JOURNAL OF SYSTEMS AND SOFTWARE 2000年第1期55卷 45-56页

作者： Ghosh, S Lee, TS Joo, SS Arizona State Univ Dept Comp Sci & Engn Tempe AZ 85287 USA Vitria Technol Sunnyvale CA 94086 USA Elect & Telecommun Res Inst Taejon 305600 South Korea

The discipline of distributed algorithms aims at distributing a computational task among multiple, concurrent processors to achieve higher throughput, efficiency, performance and other advantages. Although parallel execution time, concurrency, scalability, isoefficiency function, and speed-up have been proposed in the literature as performance metrics, the use of speed-up and its variation, scaled speed-up, dominate the literature. Speed-up is defined as the ratio of the execution time of the best known serial algorithm to the execution time of the parallel algorithm on a given number of concurrent processors. This paper analyzes critically the role of speed-up from the perspective of an emerging class of distributed algorithms, termed asynchronous, distributed, decisionmaking (ADDM) algorithms. ADDM algorithms constitute the underlying control of many real-world systems, wherein the constituent sub-components are geographically dispersed, they interact between themselves asynchronously, and are permitted autonomy in local decision-making. The term real-world implies that such systems are subject to computer control and that they relate to everyday life and are beneficial to the society in the large. Analysis reveals several key limitations of speed-up from the perspective of describing the performance of ADDM algorithms. First, by definition, speed-up utilizes the execution time of a centralized system as the basis for comparison and is, therefore, only a relative measure. The centralized implementation is obviously neither optimal nor the absolute best. Second, for many systems that are amenable to ADDM algorithms, speed-up may not constitute a relevant performance metric. This paper adopts Ferrari's definition of performance and presents a frame of reference for the performance evaluation of ADDM algorithms. While novel decision criterion may need to be developed for each ADDM algorithm, given the diversity inherent in systems, the frame of reference implies that

关键词： absolute performance asynchronous systems distributed algorithms distributed systems ideal results performance criteria absolute standard real-world systems

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Geometric Convergence of Gradient Play algorithms for distributed Nash Equilibrium Seeking

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第11期66卷 5342-5353页

作者： Tatarenko, Tatiana Shi, Wei Nedic, Angelia Arizona State Univ Sch Elect Comp & Energy Engn Phoenix AZ 85004 USA Moscow Inst Phys & Technol Dolgoprudnyi 141701 Russia

We study distributed algorithms for seeking a Nash equilibrium in a class of convex networked Nash games with strongly monotone mappings. Each player has access to her own smooth local cost function and can communicate to her neighbors in some undirected graph. To deal with fast distributed learning of Nash equilibria under such settings, we introduce a so called augmented game mapping and provide conditions under which this mapping is strongly monotone. We consider a distributed gradient play algorithm for determining a Nash equilibrium (GRANE). The algorithm involves every player performing a gradient step to minimize her own cost function while sharing and retrieving information locally among her neighbors in the network. Using the reformulation of the Nash equilibrium problem based on the strong monotone augmented game mapping, we prove the convergence of this algorithm to a Nash equilibrium with a geometric rate. Furthermore, we introduce the Nesterov type acceleration for the gradient play algorithm. We demonstrate that, similarly to the accelerated algorithms in centralized optimization and variational inequality problems, our accelerated algorithm outperforms GRANE in the convergence rate. Moreover, to relax assumptions required to guarantee the strongly monotone augmented mapping, we analyze the restricted strongly monotone property of this mapping and prove geometric convergence of the distributed gradient play under milder assumptions.

关键词： Games Nash equilibrium Convergence Cost function Acceleration distributed algorithms Symmetric matrices distributed algorithms gradient methods multi-agent systems

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distributed power control algorithms for wireless networks

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2001年第2期50卷 504-514页

作者： Wu, C Bertsekas, DP Malachite Technol Inc Methuen MA 01844 USA MIT Informat & Decis Syst Lab Cambridge MA 02135 USA

Power control has been shown to be an effective way to increase capacity in wireless systems. In previous work on power control, it has been assumed that power levels can be assigned from a continuous range. In practice, however, power levels are assigned from a discrete set. In this work, we consider the minimization of the total power transmitted over given discrete sets of available power levels subject to maintaining an acceptable signal quality for each mobile, We have developed distributed iterative algorithms for solving a more general version of this integer programming problem, which is of independent interest, and have shown that they find the optimal solution in a finite number of iterations which is polynomial in the number of power levels and the number of mobiles.

关键词： cellular networks distributed algorithms integer programming power control

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distributed disk-based algorithms for model checking very large Markov chains

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FORMAL METHODS IN SYSTEM DESIGN 2006年第2期29卷 177-196页

作者： Bell, Alexander Haverkort, Boudewijn R. Univ Twente Dept Elect Engn Math & Comp Sci NL-7500 AE Enschede Netherlands

In this paper we present data structures and distributed algorithms for CSL model checking-based performance and dependability evaluation. We show that all the necessary computations are composed of series or sums of matrix-vector products. We discuss sparse storage structures for the required matrices and present efficient sequential and distributed disk-based algorithms for performing these matrix-vector products. We illustrate the effectivity of our approach in a number of case studies in which continuous-time Markov chains (generated in a distributed way from stochastic Petri net specifications) with several hundreds of millions of states are solved on a workstation cluster with 26 dual-processor nodes. We show details about the memory consumption, the solution times, and the speedup. The distributed message-passing algorithms have been implemented in a tool called PARSECS, that also takes care of the distributed Markov chain generation and that can also be used for distributed CTL model checking of Petri nets.

关键词： Markov chains matrix-vector product disk-based algorithms state-space generation CSL model checking distributed algorithms

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Securely Solving Linear Algebraic Equations in a distributed Framework Enhanced With Communication-Efficient algorithms

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2020年第3期7卷 1027-1042页

作者： Yin, Bo Shen, Wenlong Cao, Xianghui Cheng, Yu Li, Qing IIT Dept Elect & Comp Engn Chicago IL 60616 USA Southeast Univ Sch Automat Nanjing 210096 Peoples R China Symantec Corp Mountain View CA 94043 USA

Solving linear algebraic equations (a.k.a., an LAE problem) distributedly in a network with multiple agents has wide applications in distributed control, estimation, and signal processing. A consensus-based distributed computing framework is studied in this paper. Specifically, each agent knows only a subproblem of the LAE, i.e., a subset of all equations, and then all agents apply a consensus-based algorithm to update their estimates of the correct solution of the LAE problem iteratively. Under certain conditions, it has been shown that all the estimates converge to the exact solution exponentially fast. However, such a distributed paradigm is vulnerable to malicious behaviors in an adversarial environment. In this paper, we indicate a number of security threats in this process, and thus develop robust computing solutions against those attacks. With particular attention to low storage overhead, we develop a new alternating projection method to enhance the consensus algorithm. Furthermore, we design an innovative misbehavior detection mechanism by exploiting the homomorphic signature technique. Our method can detect misbehaving agents without the common, yet sometimes infeasible, assumption of local good majority. Another significant contribution presented in this paper is an original component dropping approach for mitigating the communication overhead during the consensus process. From both theoretical and engineering perspectives, we study how the consensus can still be reached when a big portion of elements in exchanged message vectors are dropped. In our preliminary numerical results, roughly 80% data transmission can be reduced per epoch at the expense of 35% extra epochs to reach the consensus, implying 73% reduction in terms of the communication overhead.

关键词： Outsourcing distributed computing distributed algorithms Optimization Monitoring Privacy Security distributed consensus linear algebraic equations security

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Brief Announcement: Perpetual Exploration of Triangular Grid by Myopic Oblivious Robots Without Chirality 26th

Brief Announcement: Perpetual Exploration of Triangular Grid...

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26th International Symposium on Stabilization, Safety, and Security of distributed Systems

作者： Das, Raja Goswami, Pritam Sau, Buddhadeb Jadavpur Univ Kolkata India

ISBN: (纸本)9783031744976;9783031744983

Exploration of different network topologies is one of the fundamental problems of distributed systems. The problem has been studied on networks like lines, rings, tori, rectangular grids, etc. In this work, we have considered a rectangle enclosed triangular grid (RETG). A RETG is a part of an infinite triangular grid and the part is enclosed by a rectangle whose one pair of parallel sides aligns with a family of parallel straight lines of the infinite triangular grid. We have studied the problem of perpetual exploration on a RETG using oblivious robots. We have considered the robots with limited visibility i.e. the robots are myopic. Infinite visibility becomes impractical for a very large network. Limited visibility is more practical than infinite visibility. The robots have neither any chirality nor any axis agreement. An algorithm is provided to explore the RETG perpetually without any collision. The algorithm works under a synchronous scheduler. The algorithm requires three robots with two hop visibility.

关键词： Myopic robot Autonomous robots Oblivious robot Triangular grid Perpetual exploration distributed algorithms

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Fast distributed Average Consensus algorithms Based on Advection-Diffusion Processes

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第2期58卷 826-842页

作者： Sardellitti, Stefania Giona, Massimiliano Barbarossa, Sergio Univ Roma La Sapienza INFOCOM Dept I-00184 Rome Italy Univ Roma La Sapienza Dept Chem Engn I-00184 Rome Italy

distributed consensus algorithms have recently gained large interest in sensor networks as a way to achieve globally optimal decisions in a totally decentralized way, that is, without the need of sending all the data collected by the sensors to a fusion center. However, distributed algorithms are typically iterative and they suffer from convergence time and energy consumption. In this paper, we show that introducing appropriate asymmetric interaction mechanisms, with time-varying weights on each edge, it is possible to provide a substantial increase of convergence rate with respect to the symmetric time-invariant case. The basic idea underlying our approach comes from modeling the average consensus algorithm as an advection-diffusion process governing the homogenization of fluid mixtures. Exploiting such a conceptual link, we show how introducing interaction mechanisms among nearby nodes, mimicking suitable advection processes, yields a substantial increase of convergence rate. Moreover, we show that the homogenization enhancement induced by the advection term produces a qualitatively different scaling law of the convergence rate versus the network size with respect to the symmetric case.

关键词： Advection diffusion processes consensus algorithms convergence distributed algorithms sensor networks

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distributed Formation Control algorithms for QUAVs Based on Aggregative Games

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IEEE SYSTEMS JOURNAL 2023年第3期17卷 4419-4429页

作者： Deng, Zhenhua Luo, Jin Liu, Yangyang Yu, Weiyong Cent South Univ Sch Automat Changsha 410004 Peoples R China Beijing Inst Petrochem Technol Acad Artificial Intelligence Beijing 102617 Peoples R China

In this article, the formation problems of multiple quadrotor unmanned aerial vehicles (QUAVs) are studied. In contrast to existing results, the problems are investigated from the perspective of aggregative games (AGs). An interesting discovery is that the desired formation can be constituted by the Nash equilibrium of a quadratic AG. To realize the desired formation for QUAVs, we design two distributed game-based formation algorithms. With the developed algorithms, the QUAVs do not need to measure the (relative) positions and (relative) velocities of neighboring QUAVs, which differs from existing algorithms. By constructing suitable Lyapunov functions, we rigorously analyze the two formation algorithms. The first formation algorithm converges exponentially to the desired formation for the QUAVs without parameter uncertainties. The other algorithm converges asymptotically to the desired formation, even if the QUAVs contain uncertain parameters. Finally, we provide illustrative examples.

关键词： Formation control Heuristic algorithms Velocity measurement Switches Position measurement Games Control systems Aggregative games (AGs) distributed algorithms formation control multiagent systems quadrotor unmanned aerial vehicles (QUAVs)

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