An adaptive harmony search algorithm utilizing differential evolution and opposition based learning (AHS-DE-OBL) is proposed to overcome the drawbacks of the harmonysearch (HS) algorithm, such as its low fine-tuning ...
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An adaptive harmony search algorithm utilizing differential evolution and opposition based learning (AHS-DE-OBL) is proposed to overcome the drawbacks of the harmonysearch (HS) algorithm, such as its low fine-tuning ability, slow convergence speed, and easily falling into a local optimum. In AHS-DE-OBL, three main innovative strategies are adopted. First, inspired by the differential evolution algorithm, the differential harmonies in the population are used to randomly perturb individuals to improve the fine-tuning ability. Then, the search domain is adaptively adjusted to accelerate the algorithm convergence. Finally, an opposition-based learning strategy is introduced to prevent the algorithm from falling into a local optimum. The experimental results show that the proposed algorithm has a better global search ability and faster convergence speed than other selected improved harmony search algorithms and selected metaheuristic approaches.
Transmission Expansion Planning (TEP) is one of the major components of the electric power industry. In deregulated power systems, transmission systems provide the required environment for the competition among the po...
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Transmission Expansion Planning (TEP) is one of the major components of the electric power industry. In deregulated power systems, transmission systems provide the required environment for the competition among the power market participants. In this paper a mathematical model and a dynamic transmission expansion methodology is presented using an optimization framework. Investment cost, reliability (both adequacy and security), and congestion cost are considered in this optimization. To overcome the difficulties in solving the non-convex and mixed integer nature of the optimization problems, this paper offers an improved harmony search algorithm (HSA) to solve this problem. HSA was imagined using the musical process of searching for a perfect state of harmony, similar to the optimization process looks for finding a global solution that is determined by an objective function. HSA can be used to optimize a non-convex optimization problem with both continuous and discrete variables. In this paper it is shown that HSA, like other heuristic optimization algorithms, can solve the problem in a better manner compare with other methods such genetic algorithm (GA). The proposed model is applied to the IEEE 24-bus and IEEE 118-bus test systems. The obtained results show the feasibility and capability of the proposed algorithm. A comprehensive analysis of the GA methodology with the proposed method is also presented. (C) 2014 Elsevier Ltd. All rights reserved.
This paper proposes an effective global harmony search algorithm (EGHS) to solve two kinds of reliability problems: the complex (bridge) system optimization problem and the reliability-redundancy optimization problem ...
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This paper proposes an effective global harmony search algorithm (EGHS) to solve two kinds of reliability problems: the complex (bridge) system optimization problem and the reliability-redundancy optimization problem of the overspeed protection system for a gas turbine. In general, the two problems are formulated as mixed-integer nonlinear programming problems with several constraints. The EGHS combines harmony search algorithm (HS) with concepts from the swarm intelligence of particle swarm optimization algorithm (PSO) to solve optimization problems. The proposed algorithm has been applied to two typical problems with results better than previously reported. The results have demonstrated that the EGHS has strong convergence and capacity of space exploration on solving reliability optimization problems. (C) 2010 Elsevier Ltd. All rights reserved.
This paper aims to provide an optimal design of geometric parameters of a special architecture of the delta parallel mechanism, in order to improve positioning accuracy, workspace size, and kinematic and dynamic perfo...
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This paper aims to provide an optimal design of geometric parameters of a special architecture of the delta parallel mechanism, in order to improve positioning accuracy, workspace size, and kinematic and dynamic performance characteristics. In the studied 3[P2(US)] robot, the radius of both fixed and moving platforms, length of the connecting rods, and installation angle of the actuators of the manipulator are chosen as the decision variables. These parameters are optimized to maximize the weighted objective function, comprising workspace volume, global dexterity, global mass, global error, and global error sensitivity indices. Optimizations are performed employing two distinct algorithms, Genetic and harmonysearch whose results confirm each other. The optimal design of the robot leads to maximum workspace size, high dexterity, and dynamic performance, with a minimum error of the end-effector position in its reachable workspace.
Image segmentation is a process of portion image into regions. From image segmentation schemes available, multilevel thresholding on the histogram is a highly established method. Otsu's method is a significant mul...
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Image segmentation is a process of portion image into regions. From image segmentation schemes available, multilevel thresholding on the histogram is a highly established method. Otsu's method is a significant multilevel thresholding technique, in this multiple threshold levels selected on histogram and group the pixels of an image into different regions. The optimized threshold levels computed with an Optimized technique by maximizing the inter-class variance. Methods with histograms are incapable to possess spatial details of contextual information for finding optimal threshold levels. As a remedy, a novel method proposed the Energy Curve is used instead of a histogram with Otsu's method and harmony search algorithm to compute optimized gray levels. The proposed method experimented on several benchmark images, and results compared with various optimization algorithms with histogram by Dunn Index, DB Index, SD Index, mean of fitness and PSNR, comparison clarifies that the proposed method is superior to histogram-based methods. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
In wireless sensor networks, cluster head selection and routing are two well-known optimization problems associated with high computational complexity. harmony search algorithm (HSA) is one of the metaheuristics, used...
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In wireless sensor networks, cluster head selection and routing are two well-known optimization problems associated with high computational complexity. harmony search algorithm (HSA) is one of the metaheuristics, used to solve a wide range of NP-Hard problems. In this paper, first we propose an HSA-based cluster head (CH) selection algorithm by devising a fitness function with energy, distance and node degree as parameters. Next, we derived a potential function for the assignment of non-CH nodes to the CHs. Finally, an HSA-based routing algorithm is also proposed using the same parameters, i.e., energy, distance and node degree in the derivation of the fitness function. Three test cases have been considered in this study for performance evaluation. The proposed algorithm has been tested with some of the existing related techniques. Simulation results depict that the proposed algorithm (CRHS) shows superior performance over the existing techniques.
To improve the searching effectiveness of the harmonysearch (HS) algorithm, an enhanced harmony search algorithm with circular region perturbation (EHS_CRP) is proposed in this paper. In the EHS_CRP algorithm, a glob...
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To improve the searching effectiveness of the harmonysearch (HS) algorithm, an enhanced harmony search algorithm with circular region perturbation (EHS_CRP) is proposed in this paper. In the EHS_CRP algorithm, a global and local dimension selection strategy is designed to accelerate the search speed of the algorithm. A selection learning operator based on the global and local mean level is proposed to improve the balance between exploration and exploitation. Circular region perturbation is employed to avoid the algorithm stagnation and get a better exploration region. To assess performance, the proposed algorithm is compared with 10 state-of-the-art swarm intelligent approaches in a large set of global optimization problems. The simulation results confirm that EHS_CRP has a significant advantage in terms of accuracy, convergence speed, stability and robustness. Moreover, EHS_CRP performs better than other tested methods in engineering design optimization problems. Thus, the EHS_CRP algorithm is a viable and reliable alternative for some difficult and multidimensional real-world problems.
This paper presents a new hybrid natural algorithm based on harmony search algorithm (HSA) and Quantum Computing (QC). The main features of the proposed algorithm called Quantum Inspired harmony search algorithm (QIHS...
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This paper presents a new hybrid natural algorithm based on harmony search algorithm (HSA) and Quantum Computing (QC). The main features of the proposed algorithm called Quantum Inspired harmony search algorithm (QIHSA) is the integration of quantum representation scheme in the basic harmony search algorithm that allows applying successfully some quantum inspired operators like measurement and interference. This hybridization between quantum inspired computing and harmony search algorithm has led to an efficient hybrid framework which achieves better balance between the exploration of HS algorithm and the exploitation capabilities of the quantum inspired computing. Experiments on knapsack problems show the effectiveness of the proposed framework and its ability to achieve good quality solutions. (C) 2013 Elsevier B.V. All rights reserved.
This paper presents a harmony search algorithm (HSA) to solve unit commitment (UC) problem. HSA was conceptualized using the musical process of searching for a perfect state of harmony, just as the optimization proces...
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This paper presents a harmony search algorithm (HSA) to solve unit commitment (UC) problem. HSA was conceptualized using the musical process of searching for a perfect state of harmony, just as the optimization process seeks to find a global solution that is determined by an objective function. HSA can be used to optimize a non-convex optimization problem with both continuous and discrete variables. In this paper it is shown that HSA, as a heuristic optimization algorithm, may solve power system scheduling problem in a better fashion in comparison with the other evolutionary searchalgorithm that are implemented in such complicated issue. Two case studies are conducted to facilitate the effectiveness of the proposed method. One is a conventional 10-unit test system and its multiples while the other is a 26-unit system, both of which are with a 24-h scheduling horizon. Comparison of the obtained results with other approaches addressed in the literature shows the effectiveness and fastness of the proposed method.
In this article a novel approach to visual tracking called the harmony filter is presented. It is based on the harmony search algorithm, a derivative free meta-heuristic optimisation algorithm inspired by the way musi...
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In this article a novel approach to visual tracking called the harmony filter is presented. It is based on the harmony search algorithm, a derivative free meta-heuristic optimisation algorithm inspired by the way musicians improvise new harmonies. The harmony filter models the target as a colour histogram and searches for the best estimated target location using the Bhattacharyya coefficient as a fitness metric. Experimental results show that the harmony filter can robustly track an arbitrary target in challenging conditions. We compare the speed and accuracy of the harmony filter with other popular tracking algorithms including the particle filter and the unscented Kalman filter. Experimental results show the harmony filter to be faster and more accurate than both the particle filter and the unscented Kalman filter. (c) 2010 Elsevier B.V. All rights reserved.
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