Feeder reconfiguration is one of the most important tasks for loss reduction and reliability improvement in distribution networks. Most of studies so far have investigated reconfiguration problem as a static problem c...
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Feeder reconfiguration is one of the most important tasks for loss reduction and reliability improvement in distribution networks. Most of studies so far have investigated reconfiguration problem as a static problem considering fixed level of loads. This assumptions lead to suboptimal solution because of time-varying nature of loads in distribution networks. The switching operation should be cost effective and the reconfiguration scheme should balance the benefits in system loss reduction and reliability improvement against the costs of switching. Moreover, this is a dynamic problem and switching operations of time intervals over a year are not independent. This paper presents a method to determine annual feeder reconfiguration scheme considering switching costs and time-varying variables such as load profiles. In the first stage of the proposed method, to obtain effective configurations, optimal configuration for each day of year is determined independently using harmony search algorithm (HSA) and graph theory. After determination of effective configurations for the network, in the second stage, year is divided into multi equal periods and considering loss cost, interruption cost and also switching cost from a configuration to another configuration, dynamic programming algorithm (DPA) is used to find the optimum annual reconfiguration scheme. The proposed method has been tested on 95-bus distribution network and the obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically. (C) 2012 Elsevier Ltd. All rights reserved.
In this paper, selection of watermark strength in digital image using harmonysearch is presented. In image watermarking procedure, the image is divided into separate blocks and the watermark is embedded in the transf...
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In this paper, selection of watermark strength in digital image using harmonysearch is presented. In image watermarking procedure, the image is divided into separate blocks and the watermark is embedded in the transform domain via the watermark strength and the inverse transform is carried out. Digital image watermarking has several requirements based on its applications. Transparency and robustness are two important requirements in many applications. These two requirements are in conflict and watermark strength controls them. Decreasing the watermark strength causes higher transparency and lower robustness and vice versa. Having these two features is not possible at the same time, further more it would be time consuming to determine the proper watermark strength by error and trial and using the optimization algorithms is of great importance in this case. The experimental results show that the proposed algorithm selects the proper watermark strength to have suitable transparency and robustness at the same time.
The optimal utilization of multiple combined heat and power (CHP) systems is a complicated problem that needs powerful methods to solve. This paper presents a harmonysearch (HS) algorithm to solve the combined heat a...
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The optimal utilization of multiple combined heat and power (CHP) systems is a complicated problem that needs powerful methods to solve. This paper presents a harmonysearch (HS) algorithm to solve the combined heat and power economic dispatch (CHPED) problem. The HS algorithm is a recently developed meta-heuristic algorithm, and has been very successful in a wide variety of optimization problems. The method is illustrated using a test case taken from the literature as well as a new one proposed by authors. Numerical results reveal that the proposed algorithm can find better solutions when compared to conventional methods and is an efficient searchalgorithm for CHPED problem. (c) 2007 Elsevier Ltd. All rights reserved.
harmony search algorithm (HSA) is a metaheuristic method that has attracted the scientific interest since its first presentation in 2001. It is a music inspired method, imitating the music creation process in order to...
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harmony search algorithm (HSA) is a metaheuristic method that has attracted the scientific interest since its first presentation in 2001. It is a music inspired method, imitating the music creation process in order to find optimal solutions in complicated problems. HSA's successful application on single - objective optimization problems has resulted to an increasing interest in the implementation of HSA towards multiobjective optimization. The authors have adjusted HSA in order to deal successfully with multi-criteria water management problems. This adjustment has resulted to the creation of Multiobjective - HSA (MO-HSA). In addition, they have designed the multiobjective variant Polyphonic-HSA (Poly-HSA), which is inspired by the independent development of different voices in music and borrows elements from Swarm Intelligence and the single-objective variant Global-Best HSA. In the first part of this paper, both methods are presented in detail. Moreover, the performance of the proposed algorithms is evaluated using standard multiobjective test - functions. ZDT and DTLZ multiobjective tests have been chosen and indicators such as Hypervolume, C - metric and diversity metric - Delta have been used to measure the convergence to the optimal front and the diversity of the solutions obtained by the proposed methods. In the second part, MO-HSA and Poly-HSA have been introduced towards the optimization of a pump scheduling problem. The objectives considered are water supply, pumping cost, electric power peak demand and pump maintenance cost. Both methods converged to non-dominated fronts and provided excellent results which are presented in 3d figures, indicating that these methods can be effectively used in multiobjective water management problems.
This paper proposes a multi-objective harmonysearch (MONS) algorithm For optimal power flow (OPF) problem. OPF problem is formulated as a non-linear constrained multi-objective optimization problem where different ob...
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This paper proposes a multi-objective harmonysearch (MONS) algorithm For optimal power flow (OPF) problem. OPF problem is formulated as a non-linear constrained multi-objective optimization problem where different objectives and various constraints have been considered into the formulation. Fast elitist non-dominated sorting and crowding distance have been used to find and manage the Pareto optimal front. Finally, a fuzzy based mechanism has been used to select a compromise solution from the Pareto set. The proposed MONS algorithm has been tested on IEEE 30 bus system with different objectives. Simulation results are also compared with fast non-dominated sorting genetic algorithm (NSGA-II) method. It is clear from the comparison that the proposed method is able to generate :rue and well distributed Pareto optimal solutions for OPF problem. (c) 2011 Ebevier Ltd. All rights reserved.
Tool path planning is a key to ensure high machining quality and productivity in 5-axis flank milling of ruled surfaces. Previous studies have shown that optimization-driven tool path planning can effectively reduce t...
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Tool path planning is a key to ensure high machining quality and productivity in 5-axis flank milling of ruled surfaces. Previous studies have shown that optimization-driven tool path planning can effectively reduce the geometrical errors on the finished surface. However, to solve the corresponding optimization problem is a challenging task involving a large number of decision variables. This paper proposes a novel approach to generating optimized tool path for 5-axis flank finishing cut based on a geometric decomposition strategy and multi-population harmony search algorithm. The proposed approach geometrically divides the surface to be machined into a number of segments. The tool paths on those sub-surfaces are independently optimized by the multi-population harmony search algorithm. Individual tool paths are then combined together to form a complete one. The test results of representative surfaces show that the proposed approach produces higher machining precision with less computational time than compared previous methods. And the computational time is further reduced by Message passing interface based parallel computing techniques. A detailed analysis is conducted to characterize how the number of divisions affects the optimization results. And the proposed approach also shows good scalability with the increasing number of cutter locations. (C) 2018 Elsevier B.V. All rights reserved.
This paper proposes a variant of harmony search algorithm named as dispersed harmonysearch (DHS) and its application to extract the drain current (DC) and small signal model parameters of Galium Arsenide (GaAs) metal...
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This paper proposes a variant of harmony search algorithm named as dispersed harmonysearch (DHS) and its application to extract the drain current (DC) and small signal model parameters of Galium Arsenide (GaAs) metal extended semiconductor field effect transistor (MESFET). DHS algorithm is used to minimize the difference between measured and modeled (i) drain current to extract the DC model parameters and (ii) S-parameters to extract the small signal model parameters. The S-parameters are measured in the frequency range of 500 MHz to 25 GHz with a step of 500 MHz. The measured data are obtained from a fabricated MESFET of gate length 0.7 mu m and gate width of 600 mu m (4 x 150). The performance of DHS algorithm is compared with particle swarm optimization (PSO) and artificial bee colony (ABC) algorithm in terms of quality of solution and execution time to extract the model parameters. Comparison results reveal that the DHS algorithm has better convergence speed and also a robust technique for model parameter extraction compared with PSO and ABC algorithms.
A method based on harmony search algorithm (HSA) for the pattern synthesis of linear antenna arrays with the prescribed nulls is presented. Nulling of the pattern is achieved by controlling the amplitude-only, the pha...
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A method based on harmony search algorithm (HSA) for the pattern synthesis of linear antenna arrays with the prescribed nulls is presented. Nulling of the pattern is achieved by controlling the amplitude-only, the phase-only, and the position-only. The HSA is conceptualized using the musical process of searching for a perfect state of harmony. To show the effectiveness of the proposed HSA, several examples of linear antenna array patterns with the imposed single, multiple and broad nulls are given. It is found that the nulling method based on HSA is capable of steering the array nulls precisely to the undesired interference directions. The results of HSA are compared with the results of the modified touring ant colony optimization (MTACO), the bees algorithm (BA), the bacterial foraging algorithm (BFA), the plant growth simulation algorithm (PGSA), the clonal selection algorithm (CLONALG), the particle swarm optimization (1,50), the quadratic programming method (QPM), the tabu searchalgorithm (TSA), the genetic algorithm (GA), the memetic algorithm (MA), the nondominated sorting genetic algorithm 2 (NSGA-2), the multiobjective differential evolution (MODE), and the multiobjective evolutionary algorithms based on decomposition with differential evolution (MOEA/D-DE). (C) 2011 Elsevier Ltd. All rights reserved.
This brief proposes hybrid stable adaptive fuzzy controller design procedures utilizing the conventional Lyapunov theory and, the relatively newly devised harmonysearch (HS) algorithm-based stochastic approach. The o...
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This brief proposes hybrid stable adaptive fuzzy controller design procedures utilizing the conventional Lyapunov theory and, the relatively newly devised harmonysearch (HS) algorithm-based stochastic approach. The objective is to design a self-adaptive fuzzy controller, optimizing both its structures and free parameters, such that the designed controller can guarantee desired stability and simultaneously it can provide satisfactory performance with a high degree of automation in the design process. Two different variants of the hybrid controller are proposed in this work. These variants are implemented for a benchmark simulation case study and real-life experimentation. The results obtained demonstrate the usefulness of the proposed approach.
This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessa...
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This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessary means to reduce the computational cost and convergence rate of the optimization through a surrogate. This algorithm is a combination of a high quality approximation technique called Inverse Distance Weighting and a meta-heuristic algorithm called harmonysearch. The outcome is then polished by a semi-tabu searchalgorithm. This algorithm adopts a filtering system and determines solution vectors where exact simulation should be applied. The performance of the algorithm is evaluated by standard truss design problems and there has been a significant decrease in the computational effort and improvement of convergence rate.
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