Large-scale system reliability problem is a nonconvex integer nonlinear programming problem, traditional mathematical programming methods have computation limits and can not optimize an effective solution in a reasona...
详细信息
Large-scale system reliability problem is a nonconvex integer nonlinear programming problem, traditional mathematical programming methods have computation limits and can not optimize an effective solution in a reasonable time. This paper employed an amended harmony search algorithm(AHS) to solve large-scale system reliability problems. In AHS, perturbation strategy, key parameter adjustment and global dimension selection strategy are designed to balance the capability of exploitation and exploration. A comprehensive comparison is carried out to assess the search efficiency and convergence performance of AHS. Function test and large-scale system reliability case results show that AHS is superior to many previously reported well-known and excellent algorithms.
harmonysearch (HS) is a recent EA inspired by musical improvisation process to seek a pleasing harmony. Mutation is a vital component used in Evolutionary algorithms (EA) where a value in the population is randomly s...
详细信息
harmonysearch (HS) is a recent EA inspired by musical improvisation process to seek a pleasing harmony. Mutation is a vital component used in Evolutionary algorithms (EA) where a value in the population is randomly selected to be altered to improve the evolution process. The original HS algorithm applies an operation similar to mutation during the random consideration operator. During random selection operator a value within the range of the decision variable is selected randomly to explore different areas in the search space. This paper aims at experimentally evaluating the performance of HS algorithm after replacing the random consideration operator in the original HS with five different mutation methods. The different variations of HS are experimented on standard benchmark functions in terms of final obtained solution and convergence speed. The results show that using polynomial mutation improves the performance of the HS algorithm for most of the used functions. (C) 2013 Elsevier Inc. All rights reserved.
An accurate and effective technology for fault diagnosis of a high-voltage transmission line plays an important role in supporting rapid system restoration. The fault diagnosis of a high-voltage transmission line invo...
详细信息
An accurate and effective technology for fault diagnosis of a high-voltage transmission line plays an important role in supporting rapid system restoration. The fault diagnosis of a high-voltage transmission line involves three major tasks, namely fault-type identification, fault location and fault time estimation. The diagnosis problem is formulated as an optimisation problem in this work: the variables involved in the fault diagnosis problem, such as the fault location, and the unknown variables such as ground resistance, are taken into account as optimisation variables;the sum of the discrepancy of the approximation components of the actual and expected waveforms is taken as the optimisation objective. Then, according to the characteristics of the formulated optimisation problem, the harmonysearch, an effective heuristic optimisation algorithm developed in recent years, is employed to solve this problem. Test results for a sample power system have shown that the developed fault diagnosis model and method are correct and efficient.
In this paper, we use a recently proposed algorithm-novel global harmonysearch (NGHS) algorithm to solve unconstrained problems. The NGHS algorithm includes two important operations: position updating and genetic mut...
详细信息
In this paper, we use a recently proposed algorithm-novel global harmonysearch (NGHS) algorithm to solve unconstrained problems. The NGHS algorithm includes two important operations: position updating and genetic mutation with a low probability. The former can enhance the convergence of the NGHS, and the latter can effectively prevent the NGHS from being trapped into the local optimum. Based on a large number of experiments, the NGHS has demonstrated stronger convergence and stability than original harmonysearch (HS) algorithm and its two improved algorithms (IHS and SGHS). (C) 2010 Elsevier B.V. All rights reserved.
The application of chaotic sequences can be an interesting alternative to provide search diversity in an optimization procedure, named chaos optimization algorithm (COA). Since the chaotic motion is pseudorandomness a...
详细信息
The application of chaotic sequences can be an interesting alternative to provide search diversity in an optimization procedure, named chaos optimization algorithm (COA). Since the chaotic motion is pseudorandomness and chaotic sequences are sensitive to the initial conditions, the search ability of COA is usually effected by the starting values. Considering this weakness, parallel chaos optimization algorithm( PCOA) is studied in this paper. To obtain optimum solution accurately, harmony search algorithm (HSA) is integrated with PCOA to form a novel hybrid algorithm. Different chaotic maps are compared and the impacts of parallel parameter on the hybrid algorithm are discussed. Several simulation results are used to show the effective performance of the proposed hybrid algorithm. (C) 2013 Elsevier B. V. All rights reserved.
In modern power systems, efficient methods like demand side management (DSM) are needed for handling the peak load management problem. An intelligent DSM approach not only gives advantages to utilities but also provid...
详细信息
In modern power systems, efficient methods like demand side management (DSM) are needed for handling the peak load management problem. An intelligent DSM approach not only gives advantages to utilities but also provides indirect benefits to generating companies. This article introduces a combined model of multi-objective dynamic optimal power flow (MODOPF) and a game theory-based DSM technique. In this article, a single utility company and multiple residential energy consumers are considered for the game theory-based DSM technique. Here, the day ahead load shifting DSM technique is implemented with the help of a day-ahead pricing strategy and an energy consumption game. The total generation cost and transmission losses are considered as the main objectives in the proposed MODOPF problem. These two objectives were optimized individually and simultaneously using harmonysearch (HS) algorithm with different DSM participation levels for the investigation of generation side benefits. The proposed combined model was tested on two different test systems such as IEEE 30 bus and 118 bus. From the simulation results, it is clear that the combined model consisting of MODOPF and DSM is able to achieve a better economic and secure operation when compared to MODOPF alone.
For the scheduling problem of Semiconductor wafer fabrication(SWF), a new Dispatching rule based on the load balance(DRLB) is proposed. Further, a new harmonysearch(HS) algorithm based receipt priority interval(HS rp...
详细信息
For the scheduling problem of Semiconductor wafer fabrication(SWF), a new Dispatching rule based on the load balance(DRLB) is proposed. Further, a new harmonysearch(HS) algorithm based receipt priority interval(HS rpi) is presented to minimize the mean cycle time. A kind of chaotic sequence is used as the harmony vector. Then, a conversion method is designed to convert the real number harmony vector to the mixed vector representing the priorities of all receipts and the algorithm parameters. In order to increase the algorithm robustness and decrease the scale of the scheduling problem, based on receipt priority interval and DRLB, we give a special conversion method used to convert the above mixed vector to the solution of the scheduling problem of SWF. Computational simulations based on the practical instances validate the proposed algorithm.
This study presents a hybrid harmony search algorithm (HHSA) to solve engineering optimization problems with continuous design variables. Although the harmony search algorithm (HSA) has proven its ability of finding n...
详细信息
This study presents a hybrid harmony search algorithm (HHSA) to solve engineering optimization problems with continuous design variables. Although the harmony search algorithm (HSA) has proven its ability of finding near global regions within a reasonable time, it is comparatively inefficient in performing local search. In this study sequential quadratic programming (SQP) is employed to speed up local search and improve precision of the HSA solutions. Moreover, an empirical study is performed in order to determine the impact of various parameters of the HSA on convergence behavior. Various benchmark engineering optimization problems are used to illustrate the effectiveness and robustness of the proposed algorithm. Numerical results reveal that the proposed hybrid algorithm, in most cases is more effective than the HSA and other meta-heuristic or deterministic methods. (C) 2008 Elsevier B.V. All rights reserved.
In wireless sensor networks (WSNs), the location of the base station (BS) relative to sensor nodes is an important consideration in conserving network lifetime. High energy consumption mainly occurs during data commun...
详细信息
In wireless sensor networks (WSNs), the location of the base station (BS) relative to sensor nodes is an important consideration in conserving network lifetime. High energy consumption mainly occurs during data communication between sensor nodes and the BS, in both single and multi-hop infrastructures. A WSN design with dynamic BS relocation is therefore desirable as this may prolong the network operational lifetime. However, positioning the BS next to each sensor node may cause data gathering latency. The reorganization of sensor nodes into clusters and the choice of a delegate node from each cluster, known as a cluster head (CH), as a 'communicator' between each cluster and the moving BS appears to avoid this latency problem and enhance the energy utilization in WSNs. In this paper, we propose an energy-efficient network model that dynamically relocates a mobile BS within a cluster-based network infrastructure using a harmony search algorithm. First, this model allocates sensor nodes into an optimal number of clusters in which each sensor node belongs to the most appropriate cluster. Following this, the optimal CHs are chosen from the other clusters' sensors in order to evenly distribute the role of the CHs among the sensors. This infrastructure changes dynamically based on the number of alive nodes, so that load balancing is achieved among sensor nodes. Subsequently, the optimal location of the moving BS is determined between the CHs and the BS, in order to reduce the distances for communication. Finally, sensing and data transmission takes place from each sensor node to their respective CH, and CHs in turn aggregate and send this sensed data to the BS. Simulation results show very high levels of improvements in network lifetime, data delivery and energy consumption compared to static and random mobile BS network models. (C) 2016 Elsevier Inc. All rights reserved.
This paper presents an on-line variable-fidelity surrogate-assisted harmony search algorithm (VFS-HS) for expensive engineering design optimization problems. VFS-HS employs a novel model-management strategy that uses ...
详细信息
This paper presents an on-line variable-fidelity surrogate-assisted harmony search algorithm (VFS-HS) for expensive engineering design optimization problems. VFS-HS employs a novel model-management strategy that uses a multi-level screening mechanism based on non-dominated sorting to strictly control the numbers of low-fidelity and high-fidelity evaluations and to keep a balance between exploration and exploitation. The performance of VFS-HS is validated through comparison not only to those of four single-fidelity surrogate-assisted optimization methods (i.e. the particle swarm optimization algorithm with radial basis function-based surrogate (OPHS-RBF), the two-layer surrogate-assisted particle swarm optimization algorithm (TLSAPSO), the surrogate-assisted hierarchical particle swarm optimization (SH-PSO) and the hybrid surrogate-based optimization using space reduction (HSOSR)) but also to that a multi-fidelity surrogate-assisted optimization method (the multi-fidelity Gaussian process and radial basis function-model-assisted memetic differential evolution (MGPMDE)) on the CEC2014 expensive optimization test suite. A real-world problem of the optimal design for a long cylindrical gas-pressure vessel is also investigated. The results show that VFS-HS outperforms all the compared methods. (C) 2019 Elsevier B.V. All rights reserved.
暂无评论