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.
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.
In this paper, a multi-buyer multi-vendor supply chain problem is considered in which there are several products, each buyer has limited capacity to purchase products, and each vendor has warehouse limitation to store...
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In this paper, a multi-buyer multi-vendor supply chain problem is considered in which there are several products, each buyer has limited capacity to purchase products, and each vendor has warehouse limitation to store products. In this chain, the demand of each product is stochastic and follows a uniform distribution. The lead-time of receiving products from a vendor to a buyer is assumed to vary linearly with respect to the order quantity of the buyer and the production rate of the vendor. For each product, a fraction of the shortage is backordered and the rest are lost. The ordered product quantities are placed in multiple of pre-defined packets and there are service rate constraints for the buyers. The goal is to determine the reorder points, the safety stocks, and the numbers of shipments and packets in each shipment of the products such that the total cost of the supply chain is minimized. We show that the model of this problem is of an integer nonlinear programming type and in order to solve it a harmony search algorithm is employed. To validate the solution and to compare the performance of the proposed algorithm, a genetic algorithm is utilized as well. A numerical illustration and sensitivity analysis are given at the end to show the applicability of the proposed methodology in real-world supply chain problems. (C) 2011 Elsevier Inc. All rights reserved.
This paper presents a harmony search algorithm for optimal reactive power dispatch (ORPD) problem. Optimal reactive power dispatch is a mixed integer, nonlinear optimization problem which includes both continuous and ...
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This paper presents a harmony search algorithm for optimal reactive power dispatch (ORPD) problem. Optimal reactive power dispatch is a mixed integer, nonlinear optimization problem which includes both continuous and discrete control variables. The proposed algorithm is used to find the settings of control variables such as generator voltages, tap positions of tap changing transformers and the amount of reactive compensation devices to optimize a certain object. The objects are power transmission loss, voltage stability and voltage profile which are optimized separately. In the presented method, the inequality constraints are handled by penalty coefficients. The study is implemented on IEEE 30 and 57-bus systems and the results are compared with other evolutionary programs such as simple genetic algorithm (SGA) and particle swarm optimization (PSO) which have been used in the last decade and also other algorithms that have been developed in the recent years. (c) 2011 Elsevier Ltd. All rights reserved.
In this paper, a chaotic harmonysearch (CHS) algorithm is proposed to minimize makespan for the permutation flow shop scheduling problem with limited buffers. First of all, to make the harmony search algorithm suitab...
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In this paper, a chaotic harmonysearch (CHS) algorithm is proposed to minimize makespan for the permutation flow shop scheduling problem with limited buffers. First of all, to make the harmony search algorithm suitable for solving the problem under consideration, a rank-of-value rule is applied to convert continuous harmony vectors to discrete job permutations. Secondly, an efficient initialization scheme based on the Nawaz-Enscore-Ham heuristic [M. Nawaz, E.E.J. Enscore, I. Ham, A heuristic algorithm for the m-machine, n-job flow shop sequencing problem, OMEGA-International Journal of Management Science 11 (1983) 91-95] and its variants is presented to construct an initial harmony memory with a certain level of quality and diversity. Thirdly, a new improvisation scheme is developed to well inherit good structures from the best harmony vector in the last generation. In addition, a chaotic local searchalgorithm with probabilistic jumping scheme is presented and embedded in the proposed CHS algorithm to enhance the local searching ability. Computational simulations and comparisons based on the well-known benchmark instances are provided. It is shown that the proposed CHS algorithm generates better results not only than the two recently developed harmony search algorithms but also than the existing hybrid genetic algorithm and hybrid particle swarm optimization in terms of solution quality and robustness. (C) 2011 Elsevier B.V. All rights reserved.
This paper presents a new approach to determine the optimal cutting parameters leading to minimum surface roughness in face milling of X20Cr13 stainless steel by coupling artificial neural network (ANN) and harmony se...
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This paper presents a new approach to determine the optimal cutting parameters leading to minimum surface roughness in face milling of X20Cr13 stainless steel by coupling artificial neural network (ANN) and harmony search algorithm (HS). In this regard, advantages of statistical experimental design technique, experimental measurements, analysis of variance, artificial neural network and harmony search algorithm were exploited in an integrated manner. To this end, numerous experiments on X20Cr13 stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness was created using a feed forward neural network exploiting experimental data. The optimization problem was solved by harmony search algorithm. Additional experiments were performed to validate optimum surface roughness value predicted by HS algorithm. The obtained results show that the harmony search algorithm coupled with feed forward neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.
Electrical distribution network reconfiguration is a complex combinatorial optimization process aimed at finding a radial operating structure that minimizes the system power loss while satisfying operating constraints...
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Electrical distribution network reconfiguration is a complex combinatorial optimization process aimed at finding a radial operating structure that minimizes the system power loss while satisfying operating constraints. In this paper, a harmony search algorithm (HSA) is proposed to solve the network reconfiguration problem to get optimal switching combination in the network which results in minimum loss. The HSA is a recently developed algorithm which is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search which eliminates the need for derivative information. Simulations are carried out on 33- and 119-bus systems in order to validate the proposed algorithm. The results are compared with other approaches available in the literature. It is observed that the proposed method performed well compared to the other methods in terms of the quality of solution.
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 presents a new multi-objective harmonysearch (MOHS) algorithm for environmental/economic dispatch (EED) problem. The EED problem is formulated as a non linear and constrained optimization problem with comp...
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This paper presents a new multi-objective harmonysearch (MOHS) algorithm for environmental/economic dispatch (EED) problem. The EED problem is formulated as a non linear and constrained optimization problem with competing and non-commensurable objectives. The two competing objectives, fuel cost and emission, were optimized simultaneously using the proposed MONS algorithm. The MOHS algorithm uses a non dominated sorting and ranking procedure with dynamic crowding distance to develop and maintain a well distributed Pareto-optimal set. The proposed algorithm has been tested on the standard IEEE 30 bus and 118 bus systems. Simulation results are compared with the fast non dominated sorting genetic algorithm (NSGA-II) method. The results clearly show that the proposed method is able to produce a well distributed Pareto-optimal solutions than the NSGA-II method. (C) 2011 Elsevier B.V. All rights reserved.
Cost optimization of a reinforced concrete one-way joist floor system consisting of a hollow slab is presented in this paper. The cost of the system is considered to be the objective function, and the design is based ...
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Cost optimization of a reinforced concrete one-way joist floor system consisting of a hollow slab is presented in this paper. The cost of the system is considered to be the objective function, and the design is based on the American Concrete Institute's ACI 318-05 standard. This function is minimized, subject to design constraints, using the harmony search algorithm. A numerical example is presented to illustrate the performance of the algorithm and a sensitivity analysis is performed. A parametric study is also conducted to investigate the effects of the beam span and the loading on the cost optimization of the ribbed slab.
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