Coverage, one of the most important performance metrics for wireless sensor networks, reflects on how well a sensor field is monitored. Coverage problem is a devoted study of a node placement optimization problem in t...
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Coverage, one of the most important performance metrics for wireless sensor networks, reflects on how well a sensor field is monitored. Coverage problem is a devoted study of a node placement optimization problem in the coverage configuration before network deployment, where the objective is to find the optimal locations to place sensor nodes, such that the number of nodes (or the network cost) can be minimized and the coverage requirements can be satisfied. In this paper, we propose a harmonysearch (HS)-based deployment algorithm that can locate the optimal number of sensor nodes as well as their optimal locations for maximizing the network coverage and minimizing the network cost. The ability of HS is modified to automatically evolve the appropriate number of sensor nodes as well as their optimal locations. This can be accomplished by integrating the concept of adaptable length encoding in each solution vector to represent a variable number of candidate sensor nodes. Network coverage ratio, number of sensor nodes, and minimum distance between sensor nodes are the chief elements of a new objective function that has been offered to confirm the choice of the optimal number of sensor nodes and their positions. Experimental results show the ability of the proposed algorithm to find the appropriate number of sensor nodes and their locations. Furthermore, a comparative study with a metaheuristic Genetic-based algorithm and a random deployment technique has also been conducted and its results confirm the superiority of the proposed algorithm.
Clustering and routing are two key techniques to improve the energy efficiency of wireless sensor networks. As clustering and routing for improving the energy efficiency of wireless sensor networks are NP-hard problem...
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Clustering and routing are two key techniques to improve the energy efficiency of wireless sensor networks. As clustering and routing for improving the energy efficiency of wireless sensor networks are NP-hard problems, increasing meta-heuristic algorithms are introduced for solving them. However, due to their discreteness and strong constraints, most meta-heuristics are unsuitable or inefficient to optimize them. harmony search algorithm is one of the most suitable meta-heuristics for solving these problems. This article proposes a new energy-efficient clustering and routing algorithm based on harmony search algorithm to improve the energy efficiency of wireless sensor networks. The proposed approach contains two parts: clustering phase and routing phase. First, a new objective function model, which has considered balancing the energy consumption of both gateways and regular nodes as well as considered routing, is established for the clustering phase. Then, a new energy-efficient clustering algorithm is designed based on several improvements made to harmony search algorithm: (1) a discrete encoding scheme of a harmony for clustering is proposed;(2) a roulette wheel selection method is designed to choose a gateway for a regular sensor node to join, which is employed by two steps (i.e. initialization of harmony and improvisation of a new harmony);(3) the dynamically changed harmony memory considering rate is designed for improvisation of a new harmony;(4) a local search scheme is proposed to improve the best harmony within the harmony memory in iterations. In addition, the improved harmonysearch based energy-efficient routing algorithm that we proposed previously is employed to balance the energy consumption of gateways in the routing phase. The proposed approach is compared with several popular meta-heuristic-based clustering algorithms over extensive wireless sensor networks cases. The experimental results clearly demonstrate the superiority of the proposed approa
In this paper, a groundwater management model for which the solution is obtained through a coupled application of simulation and optimization models is analyzed. The most widely used numerical groundwater flow model, ...
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In this paper, a groundwater management model for which the solution is obtained through a coupled application of simulation and optimization models is analyzed. The most widely used numerical groundwater flow model, MODFLOW, which is a three-dimensional (3-D) model using the finite differences method for solving the governing groundwater flow equations, is used as the flow-simulation model. This model is then connected to the harmony search algorithm, one of the most emerging and successful metaheuristic optimization techniques, which simulates the quest for perfect harmony in music. In this paper, this technique is applied to a classic, theoretical example found in the manual of MODFLOW for comparison purposes, by examining the optimization of its aquifer system in terms of minimizing the pumping cost. For this application, a specially designed computer software programme was developed in MATLAB environment. This software, apart from coupling the simulation and optimization models, provides 2-D and 3-D graphical representations of the results allowing users to have a visual image of the piezometric surface in the whole aquifer system area. More specifically, in the specific management problem, the positions and the total required water demand for the pumping wells from the three aquifers system are pre-defined, while the optimal distribution of the pumping rates is determined through the proposed methodology. The results show that coupling flow-simulation and optimization models could be a very useful procedure when solving complex groundwater management problems.
In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the ta...
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In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the task's completion time. Accordingly, a new approach based on Pythagorean Hodograph (PH) curves and Modified harmony search algorithm is proposed to solve the two-stage path-planning problem subject to kinematic constraints such as velocity, acceleration, and minimum turning radius. First, a method of path planning based on PH curves for a single robot is proposed. Second, a mathematical model of the two-stage path-planning problem for multiple car-like robots with variable motion subject to kinematic constraints is constructed that the first-stage minimizes the total length of all paths and the second-stage minimizes the task's completion time. Finally, a modified harmony search algorithm is applied to solve the two-stage optimization problem. A set of experiments demonstrate the effectiveness of the proposed approach.
Aiming at the low recognition effect of apple images captured in a natural scene, and the problem that the OTSU algorithm has a single threshold, lack of adaptability, easily caused noise interference, and over-segmen...
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Aiming at the low recognition effect of apple images captured in a natural scene, and the problem that the OTSU algorithm has a single threshold, lack of adaptability, easily caused noise interference, and over-segmentation, an apple image recognition multi-objective method based on the adaptive harmony search algorithm with simulation and creation is proposed in this paper. The new adaptive harmony search algorithm with simulation and creation expands the search space to maintain the diversity of the solution and accelerates the convergence of the algorithm. In the search process, the harmony tone simulation operator is used to make each harmony tone evolve towards the optimal harmony individual direction to ensure the global search ability of the algorithm. Despite no improvement in the evolution, the harmony tone creation operator is used to make each harmony tone to stay away from the current optimal harmony individual for extending the search space to maintain the diversity of solutions. The adaptive factor of the harmony tone was used to restrain random searching of the two operators to accelerate the convergence ability of the algorithm. The multi-objective optimization recognition method transforms the apple image recognition problem collected in the natural scene into a multi-objective optimization problem, and uses the new adaptive harmony search algorithm with simulation and creation as the image threshold search strategy. The maximum class variance and maximum entropy are chosen as the objective functions of the multi-objective optimization problem. Compared with HS, HIS, GHS, and SGHS algorithms, the experimental results showed that the improved algorithm has higher a convergence speed and accuracy, and maintains optimal performance in high-dimensional, large-scale harmony memory. The proposed multi-objective optimization recognition method obtains a set of non-dominated threshold solution sets, which is more flexible than the OTSU algorithm in the oppo
This paper presents a harmony search algorithm with opposition-based learning techniques(HS-OBL) to solve power system. To prevent the HS-OBL algorithm from being trapped into the local optimum effectively, an impro...
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This paper presents a harmony search algorithm with opposition-based learning techniques(HS-OBL) to solve power system. To prevent the HS-OBL algorithm from being trapped into the local optimum effectively, an improved algorithm in this paper integrates the opposition-based learning operation with the improvisation process. After that, pitch adjusting rate(PAR) and harmony memory consideration rate(HMCR) are adjusted by a new adjusting strategy that is designed for dynamic adjustment to further improve the performance of algorithm. The HS-OBL is employed to solve 7 units and 14 units power system, the numerical results show that the HS-OBL has performed much better than harmonysearch(HS) algorithm and other improved algorithms that have been reported in recent literature. And the data has shown in table 4.
This paper presents a study on harmony search algorithm with application.A disadvantage of HAS is trapped into the local optimum easily,so many improved algorithms about the HAS have been presented by research ***,in ...
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This paper presents a study on harmony search algorithm with application.A disadvantage of HAS is trapped into the local optimum easily,so many improved algorithms about the HAS have been presented by research ***,in this paper,reviewed many methods published in the journals,which have been valued in some aspects,such as dynamic parameters adjustment,self-adaptive adjustment,global search and local search strategy,even the HS combined with other intelligent algorithms.
In order to enhance the performance of harmony search algorithm,a competition harmony search algorithm is presented in this *** proposed algorithm has three ***,a parallel search mechanism is designed in the improvisa...
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In order to enhance the performance of harmony search algorithm,a competition harmony search algorithm is presented in this *** proposed algorithm has three ***,a parallel search mechanism is designed in the improvisation process,which is aim to accelerate searching speed,second,a novel dimension selection strategy is presented for improving searching ***,estimation of distribution operation is used based on history *** competition updating operation is used to replace the original updating *** results demonstrated that the proposed algorithm has better performance than the state-of-the-art HS algorithms.
harmonysearch(HS) algorithm,applied in many fields,is a new population algorithm,which imitates magically the phenomenon of musical improvisation ***,it has a potential shortage,which is easily trapped into local opt...
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harmonysearch(HS) algorithm,applied in many fields,is a new population algorithm,which imitates magically the phenomenon of musical improvisation ***,it has a potential shortage,which is easily trapped into local optima when searching for global *** solve this problem,a hybrid harmony search algorithm(HHS) is promoted,which is based on the conception of swarm *** employed a local search method to replace the pitch adjusting operation,and designed an elitist preservation strategy to modify the selection *** results demonstrated that the proposed method performs much better than the HS and its improved algorithms(IHS,GHS and NGHS).
One of the important problems and active research topics in digital image precessing is image segmentation where thresholding is a simple and effective technique for this task. Multilevel thresholding is computational...
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ISBN:
(纸本)9783319689357;9783319689340
One of the important problems and active research topics in digital image precessing is image segmentation where thresholding is a simple and effective technique for this task. Multilevel thresholding is computationally complex task so different metaheuristics have been used to solve it. In this paper we propose harmony search algorithm for finding optimal threshold values in color images by Otsu's method. We tested our proposed algorithm on six standard benchmark images and compared the results with other approach from literature. Our proposed method outperformed other approach considering all performance metrics.
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