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Cuckoo Search Combined with PID Controller for Maximum Power Extraction of Partially Shaded Photovoltaic System

ENERGIES 2022年第7期15卷 2513页

作者： Al-Wesabi, Ibrahim Fang, Zhijian Farh, Hassan M. Hussein Al-Shamma'a, Abdullrahman A. Al-Shaalan, Abdullah M. Kandil, Tarek Ding, Min China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan 430074 Peoples R China Hong Kong Polytech Univ Fac Construct & Environm Dept Bldg & Real Estate Hung HomKowloon Hong Kong 999077 Peoples R China King Saud Univ Coll Engn Elect Engn Dept Riyadh 11421 Saudi Arabia Georgia Southern Univ Coll Engn & Comp Dept Elect & Comp Engn Statesboro GA 30460 USA

In the case of partial shading conditions (PSCs), normal equations cannot be completely implemented. The mathematical model of the Photovoltaic (PV) array needs to be modified and re-established with the existence of bypass diodes connected to the PV module, which can alleviate the negative effects of the PSCs and generate several peaks on the PV output characteristics curve. The first aim of this study is to modify and re-establish the mathematical model of the PV array under PSCs. Second, it aims to improve and validate the reliable Cuckoo Search Algorithm (CSA) by integrating it with PID (hybrid CSA-PID) to diminish the impact of PSCs problems. The hybrid CSA-PID was proposed to both track the global maximum power point (GMPP) of PV systems and reduce the tracking time to eliminate the fluctuations around the GMPP. Further, the PID controller was used to eliminate the error percentage obtained by CSA under PSCs to generate the required duty cycle, which provides the required and desired maximum voltage accordingly. The proposed CSA-PID technique has been implemented using both Matlab/Simulink and Hardware-In-Loop experiments on the MT real-time control platform NI PXIE-1071. For validation, the Hybrid CSA-PID method is evaluated and compared with CSA, modified particle swarm optimization (MPSO), PSO, and modified perturb and observe (MP&O) methods under similar conditions. Finally, the obtained findings demonstrated the efficacy and superiority of the proposed hybrid CSA-PID technique, demonstrating its resilience, fast reaction, and good performance in terms of tracking time and GMPP tracking.

关键词： photovoltaic system MPPT partial shading conditions Hybrid CSA-PID heuristics algorithms hardware-in-loop

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Connectivity Recovery Based on Boundary Nodes and Spatial Triangle Fermat Points for Three-Dimensional Wireless Sensor Networks

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SENSORS 2024年第24期24卷 7876页

作者： Chen, Hongsheng Shi, Ke Hubei Univ Sci & Technol Coll Comp Sci & Technol Xianning 437100 Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China

In recent years, wireless sensor networks have been widely used, especially in three-dimensional environments such as underwater and mountain environments. However, in harsh environments, wireless sensor networks may be damaged and split into many isolated islands. Therefore, restoring network connectivity to transmit data effectively in a timely manner is particularly important. However, the problem of finding the minimum relay nodes is NP-hard, so heuristics methods are preferred. This paper presents a novel connectivity recovery strategy based on boundary nodes and spatial triangle Fermat points for three-dimensional wireless sensor networks. The isolated islands are represented as the boundary nodes, and the connectivity recovery problem is modeled as a graph connectivity problem. Three heuristics algorithms-the variant Kruskal algorithm, the variant Prim algorithm, and the spatial triangle Fermat point algorithm-are proposed to solve this problem. The variant Kruskal algorithm and the variant Prim algorithm connect the isolated islands by constructing the minimum spanning tree to link all the boundary nodes and placing relay nodes along the edges of this tree. We derive an accurate formula to determine the coordinates of spatial triangle Fermat points. Based on this formula, the spatial triangle Fermat point algorithm constructs a Steiner tree to restore network connectivity. Extensive simulation experiments demonstrate that our proposed algorithms perform better than the existing algorithm.

关键词： three-dimensional wireless sensor networks connectivity recovery spatial triangle Fermat points heuristics algorithms boundary nodes

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Identifying influential spreaders in complex networks through local effective spreading paths

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2017年第5期2017卷 053402-053402页

作者： Wang, Xiaojie Zhang, Xue Yi, Dongyun Zhao, Chengli Natl Univ Def Technol Coll Sci Changsha 410073 Hunan Peoples R China Natl Univ Def Technol State Key Lab High Performance Comp Changsha 410073 Hunan Peoples R China

How to effectively identify a set of influential spreaders in complex networks is of great theoretical and practical value, which can help to inhibit the rapid spread of epidemics, promote the sales of products by word-of-mouth advertising, and so on. A naive strategy is to select the top ranked nodes as identified by some centrality indices, and other strategies are mainly based on greedy methods and heuristic methods. However, most of those approaches did not concern the connections between nodes. Usually, the distances between the selected spreaders are very close, leading to a serious overlapping of their influence. As a consequence, the global influence of the spreaders in networks will be greatly reduced, which largely restricts the performance of those methods. In this paper, a simple and effcient method is proposed to identify a set of discrete yet influential spreaders. By analyzing the spreading paths in the network, we present the concept of effective spreading paths and measure the influence of nodes via expectation calculation. The numerical analysis in undirected and directed networks all show that our proposed method outperforms many other centrality-based and heuristic benchmarks, especially in large-scale networks. Besides, experimental results on different spreading models and parameters demonstrates the stability and wide applicability of our method.

关键词： heuristics algorithms random graphs networks data mining optimization over networks

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Quenches in the Sherrington-Kirkpatrick model

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2024年第8期2024卷 083302-083302页

作者： Erba, Vittorio Behrens, Freya Krzakala, Florent Zdeborova, Lenka ?Ecole Polytech Federalede Lausanne EPFL Stat Phys Computat Lab CH-1015 Lausanne Switzerland ?Ecole Polytech Federalede Lausanne EPFL Informat Learning & Phys Lab CH-1015 Lausanne Switzerland

The Sherrington-Kirkpatrick model is a prototype of a complex non-convex energy landscape. Dynamical processes evolving on such landscapes and locally aiming to reach minima are generally poorly understood. Here, we study quenches, i.e. dynamics that locally aim to decrease energy. We analyse the energy at convergence for two distinct algorithmic classes, single-spin flip and synchronous dynamics, focusing on greedy and reluctant strategies. We provide precise numerical analysis of the finite size effects and conclude that, perhaps counter-intuitively, the reluctant algorithm is compatible with converging to the ground state energy density, while the greedy strategy is not. Inspired by the single-spin reluctant and greedy algorithms, we investigate two synchronous time algorithms, the sync-greedy and sync-reluctant algorithms. These synchronous processes can be analysed using dynamical mean field theory (DMFT), and a new backtracking version of DMFT. Notably, this is the first time the backtracking DMFT is applied to study dynamical convergence properties in fully connected disordered models. The analysis suggests that the sync-greedy algorithm can also achieve energies compatible with the ground state, and that it undergoes a dynamical phase transition.

关键词： spin glasses cavity and replica method heuristics algorithms energy landscapes

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Belief propagation guided decimation algorithms for random constraint satisfaction problems with growing domains

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2021年第3期2021卷

作者： Zhao, Chun-Yan Fu, Yan-Rong Univ Shanghai Sci & Technol Coll Sci Shanghai 200093 Peoples R China

We propose three kinds of belief propagation (BP) guided decimation algorithms using asynchronous updating strategy to solve a prototype of random constraint satisfaction problem with growing domains referred to as model RB. For model RB, the exact satisfiability phase transitions have been established rigorously, and almost all instances are intrinsic hard in the transition region. Finding solutions of a random instance of model RB is very challenging, and the problem size is limited to 10(2). The BP guided decimation algorithms we proposed are called asynchronous updating belief propagation (ABP) algorithm, asynchronous updating belief propagation* (ABP*) algorithm, and asynchronous updating belief propagation with variable order (VABP) algorithm, respectively. In the BP part of the algorithms, we adopt asynchronous updating strategy to obtain the latest passing messages between constraints and variables, which can improve the convergence of BP equations. We also use a damping factor that adds the old messages with a certain weight into the new messages sent from variables to constraints, to reduce the occurrence of oscillation during the convergence of BP equations. In the ABP algorithm, we compute the marginal probability distribution of all variables according to the messages obtained after the BP equations converge, then select the most biased variable and fix its value on the component with the maximum probability. While the ABP* algorithm considers how to continue the decimation process if the BP equations do not converge. Different from the previous two algorithms, in the VABP algorithm, we first choose a random order of the variables, and then assign values to the variables according to the given order after BP converges. Experimental results suggest that the three kinds of BP guided decimation algorithms appear to be very effective in solving random instances of model RB even when the constraint tightness is close to the theoretical satisfiability thresho

关键词： analysis of algorithms heuristics algorithms message-passing algorithms belief propagation

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Finding network communities using modularity density

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2016年第12期2016卷 123402-123402页

作者： Botta, Federico del Genio, Charo I. Univ Warwick Ctr Complex Sci Coventry CV4 7AL W Midlands England Univ Warwick Sch Life Sci Coventry CV4 7AL W Midlands England

Many real-world complex networks exhibit a community structure, in which the modules correspond to actual functional units. Identifying these communities is a key challenge for scientists. A common approach is to search for the network partition that maximizes a quality function. Here, we present a detailed analysis of a recently proposed function, namely modularity density. We show that it does not incur in the drawbacks su. ered by traditional modularity, and that it can identify networks without ground-truth community structure, deriving its analytical dependence on link density in generic random graphs. In addition, we show that modularity density allows an easy comparison between networks of di. erent sizes, and we also present some limitations that methods based on modularity density may su. er from. Finally, we introduce an e. cient, quadratic community detection algorithm based on modularity density maximization, validating its accuracy against theoretical predictions and on a set of benchmark networks.

关键词： Random graphs networks Analysis of algorithms heuristics algorithms Typical-case computational complexity

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Entropy production rate as a criterion for inconsistency in decision theory

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2018年第5期2018卷

作者： Dixit, Purushottam D. Columbia Univ Dept Syst Biol New York NY 10027 USA

Individual and group decisions are complex, often involving choosing an apt alternative from a multitude of options. Evaluating pairwise comparisons breaks down such complex decision problems into tractable ones. Pairwise comparison matrices (PCMs) are regularly used to solve multiple-criteria decision-making problems, for example, using Saaty's analytic hierarchy process (AHP) framework. However, there are two significant drawbacks of using PCMs. First, humans evaluate PCMs in an inconsistent manner. Second, not all entries of a large PCM can be reliably filled by human decision makers. We address these two issues by first establishing a novel connection between PCMs and time-irreversible Markov processes. Specifically, we show that every PCM induces a family of dissipative maximum path entropy random walks (MERW) over the set of alternatives. We show that only 'consistent' PCMs correspond to detailed balanced MERWs. We identify the non-equilibrium entropy production in the induced MERWs as a metric of inconsistency of the underlying PCMs. Notably, the entropy production satisfies all of the recently laid out criteria for reasonable consistency indices. We also propose an approach to use incompletely filled PCMs in AHP. Potential future avenues are discussed as well.

关键词： heuristics algorithms inference in socio-economic system

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Multi-resource scheduling and routing for emergency recovery operations

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2020年 50卷 101780页

作者： Bodaghi, Behrooz Shahparvari, Shahrooz Fadaki, Masih Lau, Kwok Hung Ekambaram, Palaneeswaran Chhetri, Prem Swinburne Univ Technol Fac Sci Engn & Technol Hawthorn Vic Australia RMIT Univ Sch Accounting Informat Syst & Supply Chain Melbourne Vic Australia

Efficient delivery of multiple resources for emergency recovery during disasters is a matter of life and death. Nevertheless, most studies in this field only handle situations involving single resource. This paper formulates the Multi-Resource Scheduling and Routing Problem (MRSRP) for emergency relief and develops a solution framework to effectively deliver expendable and non-expendable resources in Emergency Recovery Operations. Six methods, namely, Greedy, Augmented Greedy, k-Node Crossover, Scheduling. Monte Carlo, and Clustering, are developed and benchmarked against the exact method (for small instances) and the genetic algorithm (for large instances). Results reveal that all six heuristics are valid and generate near or actual optimal solutions for small instances. With respect to large instances, the developed methods can generate near-optimal solutions within an acceptable computational time frame. The Monte Carlo algorithm, however, emerges as the most effective method. Findings of comprehensive comparative analysis suggest that the proposed MRSRP model and the Monte Carlo method can serve as a useful tool for decision-makers to better deploy resources during emergency recovery operations.

关键词： Expendable resources Non-expendable resources Emergency recovery operations Multi-resource scheduling heuristics algorithms Clustering algorithm Coronavirus outbreak case

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Multi-level spectral graph partitioning method

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JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT 2017年第9期2017卷

作者： Talu, Muhammed Fatih Inonu Univ Comp Sci Dept Malatya Turkey

In this article, a new method for multi-level and balanced division of non-directional graphs (MSGP) is introduced. Using the eigenvectors of the Laplacian matrix of graphs, the method has a spectral approach which has superiority over local methods (Kernighan-Lin and Fiduccia-Mattheyses) with a global division ability. Bisection, which is a spectral method, can divide the graph by using the Fiedler vector, while the recursive version of this method can divide into multiple levels. However, the spectral methods have two disadvantages: (1) high processing costs;(2) dividing the sub-graphs independently. With a better understanding of the eigenvectors of the whole graph, and by discovering the confidential information owned, MSGP can divide the graphs into balanced and multi-leveled without recursive processing. Inspired by Haar wavelets, it uses the eigenvectors with a binary heap tree. The comparison results in seven existing methods (some are community detection algorithms) on regular and irregular graphs which clearly demonstrate that MSGP works about 14,4 times faster than the others to produce a proper partitioning result.

关键词： random graphs networks clustering techniques heuristics algorithms

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