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Renewable Energy Integration into Smart Grids: A Multidisciplinary Approach to Technology Modelling and Simulation (ICREISG), International Conference on

作者： S. K. Barik S.K. Mohapatra A.K. Patra SEC Mayurbhanja Odisha India GCE Keonjhar Odisha India

ISBN: (数字)9781728170343

ISBN: (纸本)9781728170350

pattern search (PS) algorithm is proposed to design a STATCOM controller FACTS based transient stability in this paper. To avoid the disadvantage remote signal that may possibly affect consistency of the controller, a locally measured line active power equivalent to remote speed variation signal is the modified signal given to controller input. The stability performance is enhance by optimization of the controller's parameter of the power system. The responses of the projected controllers are applied to both SMIB and 3-machine power system considering several transient disturbances. On comparing with different input signal with different fault and three operating condition, the MATLAB simulation results are presented. It is concluded that the damping of the power system is greatly enhanced in the case of modified local signal is measured rather than local and remote input signals.

关键词： STATCOM pattern search algorithm damping oscillations power system stability Modified Local Signal Static compensator input signal Power system stability power systems damped oscillation Controllers pattern search absorption of shock single machine infinite bus system signals

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pattern search algorithms for mixed variable programming

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SIAM JOURNAL ON OPTIMIZATION 2001年第3期11卷 573-594页

作者： Audet, C Dennis, JE Ecole Polytech GERAD Dept Math & Genie Ind Montreal PQ H3C 3A7 Canada Rice Univ Dept Computat & Appl Math Houston TX 77005 USA

Many engineering optimization problems involve a special kind of discrete variable that can be represented by a number, but this representation has no significance. Such variables arise when a decision involves some situation like a choice from an unordered list of categories. This has two implications: The standard approach of solving problems with continuous relaxations of discrete variables is not available, and the notion of local optimality must be defined through a user-specified set of neighboring points. We present a class of direct search algorithms to provide limit points that satisfy some appropriate necessary conditions for local optimality for such problems. We give a more expensive version of the algorithm that guarantees additional necessary optimality conditions. A small example illustrates the differences between the two versions. A real thermal insulation system design problem illustrates the efficacy of the user controls for this class of algorithms.

关键词： pattern search algorithm convergence analysis bound constrained optimization mixed variable programming derivative-free optimization

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Solving economic machining models using quantum-pattern search-particle swarm hybrid optimization algorithm

Solving economic machining models using quantum-pattern sear...

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11th IASTED International Conference on Artificial Intelligence and Soft Computing

作者： Alfares, Fawzan S. Alenezi, Hussein Alajmi, Mahdi S. Department of Manufacturing Engineering PAAET Kaifan P.O. Box: 68425 Kuwait School of Engineering and Design Brunel University Uxbridge Middlesex UB8 3PH United Kingdom

ISBN: (纸本)9780889866935

This paper introduce novel hybrid optimization algorithm consists from elements of three optimization algorithms. The first algorithm is the particle swarm optimization, in which the element "velocity" is used. This element provides the distance to jump from the current position to the new position. The second element acquired from the pattern search algorithm in which the movement of the solution candidate in the neighborhood performed. This movement called compass movement where the direction of movement is to the up, down, right, or left. The last element obtained from the quantum-inspired algorithm. This element says that if no best solution found after perforining the compass movement then the solution candidate will move to one of these positions that have the highest probability. The formula of the probabilities based on quantum computing theory. To investigate the performance of the proposed algorithm, machining economic models are used. The results have showed promising application of this hybrid algorithm to the field of mechanical engineering.

关键词： optimization evolution algorithms quantum theory pattern search algorithm and particle swarm optimization

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Genetic algorithm-Driven Cover Set Scheduling for Longevity in Wireless Sensor Networks

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2025年第3期16卷 1104-1112页

作者： Larhlimi, Ibtissam Lmkaiti, Mansour Lachgar, Maryem Ouchitachen, Hicham Darif, Anouar Limati, Hicham Mouncif Sultan Moulay Slimane Univ LAB Polydisciplinary Fac Khouribga Morocco

This paper aims to develop an efficient scheduling approach based on Genetic algorithms to optimize energy consumption and maximize the operational lifetime of Wireless cial for prolonging the operational lifespan of wireless sensor networks (WSNs) that include a substantial number of sensors. Simultaneously activating all sensors results in a fast depletion of energy, thus diminishing the overall lifespan of the network. To address this issue, it is necessary to schedule sensor activity in an effective manner. This task, known as the maximum coverage set scheduling (MCSS) problem, is highly complex and has been demonstrated to be NP-hard. This article presents a customized genetic algorithm designed to tackle the MCSS problem, aiming to improve the longevity of Wireless Sensor Networks (WSNs). Our methodology effectively detects and enhances combinations of coverage sets and their corresponding schedules. The program incorporates key criteria such as the detection ranges of individual sensors, their energy levels, and activity durations to optimize the overall energy efficiency and operational sustainability of the network. The performance of the suggested algorithm is assessed through simulations and compared to that of the Greedy algorithm and the pattern search algorithm. The results indicate that our genetic algorithm not only maximizes network lifetime but also enhances the efficiency and efficacy of solving the MCSS problem. This represents a significant improvement in managing the energy consumption in WSNs.

关键词： Maximum network lifetime wireless sensor network coverage sets scheduling genetic algorithm pattern search algorithm

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Damage detection in plates based on pattern search and Genetic algorithms

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SMART STRUCTURES AND SYSTEMS 2011年第2期7卷 117-132页

作者： Amiri, G. Ghodrati Razzaghi, S. A. Seyed Bagheri, A. Iran Univ Sci & Technol Sch Civil Engn Ctr Excellence Fundamental Studies Struct Engn Tehran 16846 Iran

This paper is aimed at presenting two methods on the basis of pattern search and genetic algorithms to detect and estimate damage in plates using the modal data of a damaged plate. The proposed methods determine the damages of plate structures using optimization of an objective function by pattern search and genetic algorithms. These methods have been applied to two numerical examples, namely four-fixed supported and cantilever plates with and without noise in the modal data and containing one or several damages. The obtained results clearly reveal that the proposed methods can be viewed as a powerful and reliable method for structural damage detection in plates using the modal data.

关键词： damage detection plate pattern search algorithm genetic algorithm modal data

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A pattern search filter method for nonlinear programming without derivatives

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SIAM JOURNAL ON OPTIMIZATION 2004年第4期14卷 980-1010页

作者： Audet, C Dennis, JE Ecole Polytech GERAD Montreal PQ H3C 3A7 Canada Ecole Polytech Dept Math & Genie Ind Montreal PQ H3C 3A7 Canada Rice Univ Dept Appl & Computat Math Houston TX 77005 USA

This paper formulates and analyzes a pattern search method for general constrained optimization based on filter methods for step acceptance. Roughly, a filter method accepts a step that improves either the objective function value or the value of some function that measures the constraint violation. The new algorithm does not compute or approximate any derivatives, penalty constants, or Lagrange multipliers. A key feature of the new algorithm is that it preserves the division into search and local poll steps, which allows the explicit use of inexpensive surrogates or random search heuristics in the search step. It is shown here that the algorithm identifies limit points at which optimality conditions depend on local smoothness of the functions and, to a greater extent, on the choice of a certain set of directions. Stronger optimality conditions are guaranteed for smoother functions and, in the constrained case, for a fortunate choice of the directions on which the algorithm depends. These directional conditions generalize those given previously for linear constraints, but they do not require a feasible starting point. In the absence of general constraints, the proposed algorithm and its convergence analysis generalize previous work on unconstrained, bound constrained, and linearly constrained generalized pattern search. The algorithm is illustrated on some test examples and on an industrial wing planform engineering design application.

关键词： pattern search algorithm filter algorithm surrogate-based optimization derivative-free convergence analysis constrained optimization nonlinear programming

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Second-order behavior of pattern search

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SIAM JOURNAL ON OPTIMIZATION 2005年第2期16卷 515-530页

作者： Abramson, MA USAF Inst Technol Dept Math & Stat AFIT ENC Wright Patterson AFB OH 45433 USA

Previous analyses of pattern search algorithms for unconstrained and linearly constrained minimization have focused on proving convergence of a subsequence of iterates to a limit point satisfying either directional or first-order necessary conditions for optimality, depending on the smoothness of the objective function in a neighborhood of the limit point. Even though pattern search methods require no derivative information, we are able to prove some limited directional second-order results. Although not as strong as classical second-order necessary conditions, these results are stronger than the first-order conditions that many gradient-based methods satisfy. Under fairly mild conditions, we can eliminate from consideration all strict local maximizers and an entire class of saddle points.

关键词： nonlinear programming pattern search algorithm derivative-free optimization convergence analysis second-order optimality conditions

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Control of Supply Risk Based on Ranking Foreign Suppliers Using pattern search Weighted Fuzzy Comprehensive Evaluation

Control of Supply Risk Based on Ranking Foreign Suppliers Us...

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2nd International Joint Conference on Computational Sciences and Optimization

作者： Yang, Lei Liu, Cheng Zhang, Zhiyong Shi, Yongqiang S China Univ Technol Dept Logist Engn & Management Sch Econ & Commerce Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9780769536057

Essential characteristics of foreign suppliers are identified that should be considered in the supplier selection process to control supply chain disruption risk in the manufacturer's assembly operation. Since that the tangible and intangible characteristics are integrated in the supplier-ranking procedure and the multi-criteria evaluation system is introduced while the weight of each criteria may not be known in advance, in this paper, the fuzzy comprehensive evaluation(FCE) is employed to settle the prompt break skip illogicality of the membership degree of supplier' performance to a reliability level, and the pattern search algorithm (PSA) is imposed to figure out the significant weights to make full use of existing well-known benchmark supplier selected by consultants and manufacturer's executives in group-decision rather than completely subjective preferring determination by persons. A case study is presented in which a manufacturer ranks its current foreign supplier against two other potentials based on criterions of supply reliability. The outcome illustrates the practicality of the pattern search weighted FCE method's application in the selection strategy of foreign business partners.

关键词： supplier selection supply chain risk control pattern search algorithm group decision-making fuzzy comprehensive evaluation

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Efficient latency-and-energy-aware IoT-fog-cloud task orchestration: novel algorithmic approach with enhanced arithmetic optimization and pattern search

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International Journal of Information Technology (Singapore) 2024年第5期16卷 3311-3324页

作者： Srichandan, Suresh Kumar Majhi, Santosh Kumar Jena, Sudarson Mishra, Kaushik Rao, D. Chandrasekhar Sambalpur University Institute of Information Technology Sambalpur University Jyotivihar Odisha Burla 768019 India Veer Surendra Sai University of Technology Odisha Burla 768018 India Department of Computer Science and Information Technology Guru Ghasidas Vishwavidyalaya Koni C.G. Bilaspur 495009 India Gandhi Institute of Technology and Management Andhra Pradesh Visakhapatnam 530045 India

Nowadays, the load on datacenters has become more and more due to the unprecedented growth of diversified data from many IoT devices;hence, resource utilization has become more difficult. So, Cloud computing emerged as an appealing solution to leverage IoT devices' computational, memory, capacity and resource constraints. However, the physical gap between IoT devices and the Cloud datacentre resulted in latency overhead and incurred high energy consumption due to the centralized nature of datacenter. Thus, Fog computing is introduced as a complementary to Cloud computing to minimize the physical gap and thus, latency by bringing the computations closer to the end devices. However, the placement of tasks to a particular Fog node (FN)/cloud virtual machine (VM) is an NP-hard problem with much higher computational time. Thus, metaheuristic algorithms are a way out as they have a polynomial time complexity. The arithmetic optimization algorithm (AOA) along with the pattern search algorithm is one of the optimization algorithms, implemented in order to minimise the makespan and maximise resource utilization. This paper proposes an improved AOA when combined with a pattern search algorithm helps in migrating the tasks from an overloaded FN to an underloaded FN more effectively. Finally, the proposed algorithm is compared with similar optimization algorithms on various parameters. From the simulations, it is evident that the proposed AOA-PS-based task scheduling approach outperformed others with a percentage of improvement of 24.2%, 18.6%, 16%, 5.4%, and 23.4% for makespan, resource utilization, response time, energy consumption, and degree of imbalance, respectively. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Arithmetic optimization algorithm Cloud computing Fog computing IoT pattern search algorithm Resource management Task orchestration

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Optimization of multilateral well trajectories using pattern search and genetic algorithms

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RESULTS IN ENGINEERING 2022年 16卷

作者： Ghadami, Shahra Biglarian, Hassan Biglarian, Hossein Salimi, Mohsen Sharif Univ Technol Sch Mech Engn Tehran Iran Res Inst Petr Ind RIPI Energy Res Div Tehran Iran Res Inst Petr Ind RIPI Upstream & Explorat Res Div Tehran Iran Niroo Res Inst NRI Renewable Energy Res Dept Tehran Iran

Multilateral well is a promising technology in developing oil reservoirs. Because this technology may increase the production rate per well and reduce the costs of field development, it is rapidly replacing the old methods. This study uses a three-dimensional line-source model with direct search methods, including pattern search and genetic algorithms to optimize the well trajectories. This method was applied to several cases, with different forms of wells and reservoirs. In all cases, significant improvement was observed in the production rate. Furthermore, the production enhancement using the optimized well trajectories which have curved-paths is compared to the case with linear well trajectories. It was shown that at least a 6% production increase is possible for the curved trajectory well with respect to the well with the constant slope lines. Besides, it was illustrated that the oil production is boosted solely by altering the slope of the well or its laterals along the well path.

关键词： Multilateral wells Line -source model Unconventional wells optimization Genetic algorithm pattern search algorithm

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