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27th Chinese Control and Decision Conference, CCDC 2015

作者： Zhang, Ping Haibin, Ouyang Gao, Liqun Physics Department Anshan Normal University Anshan China Information Engineering Department LiaoNing Provincial College of Communications Shenyang China

ISBN: (纸本)9781479970179

harmony search (HS) algorithm is a population-based meta-heuristic algorithm, which is conceptualized using the musical improvisation process of searching for a perfect state of harmony. In this paper, an improved harmony search algorithm with perturbation strategy is proposed to enhance the global and local search ability of HS algorithm. A perturbation strategy is presented to improve global search capability. Local opposition-based learning is used to replace pitch adjustment, which aims to enhance local search ability. In addition, elite memory is designed to further escape local minima. Numerical results indicated that the proposed IHSP algorithm has better performance than the state-of-the-art HS algorithms. © 2015 IEEE.

关键词： Elite memory harmony search algorithm Opposition-based learning Perturbation strategy

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Comparison of harmony search algorithm, Improved harmony search algorithm with Biogeography Based Optimization algorithm for Solving Constrained Economic Load Dispatch Problems

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Procedia Technology 2015年 21卷 611-618页

作者： P. Karthigeyan M. Senthil Raja R. Hariharan S. Prakash S. Delibabu R. Gnanaselvam Project Associate I.I.T Madraschennai-600036 India Assistant Professor VI Institute of technology chennai-603108 India PG Scholar SRM University chennai-603203 India Assistant Professor Parisutham Institute of technology and science Thanjavur Tamil Nadu-613006 India Assistant Professor Sri Andal alagar college of Engineeringchennai-603111 India

This paper presents comparison of harmony search algorithm (HSA), improved harmony search (IHS) algorithm, Biogeography based optimization (BBO) algorithm for solving constrained economic load dispatch problems in the power system. In the IHS algorithm multiple harmony memory consideration rates and dynamic pitch adjusting rate are used to generate new solution vector. This proposed algorithms have been successfully tested in the test system which consists of twenty generating units with ramp rate limits and valve point loading constraint. The results obtained through the simulation results reveal that IHS algorithm has minimum total fuel cost and has good convergence characteristics when compared to both harmony search algorithm and Biogeography based optimization algorithm.

关键词： Improved harmony search algorithm harmony search algorithm Biogeography based optimization algorithm Economic Load Dispatch Ramp Rate limits valve point loading constraints.

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Optimal Placement and Sizing of DSTATCOM Using harmony search algorithm

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Energy Procedia 2015年 79卷 759-765页

作者： T. Yuvaraj K.R. Devabalaji K. Ravi School of Electrical Engineering VIT University Vellore 632014 India

This paper investigates a new approach to find the optimal location and sizing of Distribution STATic COMpensator (DSTATCOM) with an objective function of minimizing the total network power losses. harmony search algorithm is used to find the optimal location and sizing of DSTATCOM. The proposed work is tested on standard IEEE 33-bus radial distribution systems. The obtained result shows that optimal placement and sizing of DSTATCOM in the radial distribution network effectively reduces the total power losses of the system.

关键词： Distribution STATic COMpensator (DSTATCOM) harmony search algorithm Radial Distribution Network.

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Join query optimisation in the distributed databases using a hybrid harmony search and artificial bee colony algorithm

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2021年第3期17卷 189-198页

作者： Yazdani, Manizheh Navimipour, Nima Jafari Islamic Azad Univ Dept Comp Engn Tabriz Branch Tabriz Iran Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan

The query optimiser is a vital part of any distributed database mechanism. Reducing the execution period of the query depends on reaching an ideal query execution plan. Due to this issue's NP-hard nature, a hybrid harmony search and an artificial bee colony algorithm can be useful. The harmony is used to call query plans and signify them by S-dimension real vectors. A harmony memory is a place for creating and storing a primary population of harmony vectors. Then, bees explore harmony memory as a food source. The production of a novel nominate harmony out of all query plans in the harmony memory requires a pitch adjustment principle, a memory consideration one, and a random re-initialisation. Lastly, the new candidate vector replaces the worst harmony vector when it works better. The simulation outcomes have indicated that the introduced method reduces the expenses of evaluating a query compared to the harmony search and bee colony optimisation algorithms. However, this method has a longer execution time.

关键词： distributed database system join query optimisation harmony search algorithm artificial bee colony

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Hybridizing sine-cosine algorithm with harmony search strategy for optimization design problems

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SOFT COMPUTING 2021年第16期25卷 11053-11075页

作者： Singh, Narinder Kaur, Jaspreet Punjabi Univ Dept Math Patiala Punjab India Baba Farid Coll Dept Comp Sci Bathinda India

Recent developments designate the quick growing of optimization meta-heuristics in the domain of optimization. Sine-cosine optimizer is a stochastic technique that generates various preliminary random research agents global optimal solutions and involves them to fluctuate toward or outwards the superior global optima solution utilizing a mathematical model based on sine and cosine trigonometry functions. Nevertheless, standard SCA provides insufficient global optima results on complex dimension functions illustrating poor convergence rate. The search process of the SCA method holds various shortcomings such as slow convergence, weak balance amid exploration and exploitation, and inefficiency in convergence. To overcome these shortcomings in this work, we are trying to present a new heuristic approach based on merging the features of SCA (sine-cosine approach) with a HS (harmony search approach) known as HSCAHS algorithm. The existing approach integrates the merits of the sine-cosine algorithm and HS algorithm to reduce demerits, like the trapping in local optima and unbalanced exploitation. The new approach presents own work performance in two different stages;firstly, the sine-cosine algorithm starts the explore procedure to augment exploration capability. Secondly, harmony search part starts its search from SCA finds so far to augment the exploitation tendencies. Hence, hybrid approach can find best possible solution in which least time improves the exploitation and exploration. Hence, the newly existing hybrid approach can be quickly convergent, statistically sound and more robust. The capability of the hybrid approach is verified by applying it on eighteen tested benchmark, economic dispatch, three-bar truss design, rolling element bearing design, multiple disc clutch brake design, speed reducer design and planetary gear train design problems. The experimental solutions reveal that the hybrid approach is able to finding the superior quality of optimal goal (or s

关键词： Standard optimization function Heuristic hybridization Exploration Exploitation Sine-cosine harmony search algorithm

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Improved harmony search algorithm with Perturbation Strategy

Improved Harmony Search Algorithm with Perturbation Strategy

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第27届中国控制与决策会议

作者： Ping Zhang Haibin Ouyang Liqun Gao Physics Department Anshan Normal University Information engineering department LiaoNing provincial College of Communications

ISBN: (纸本)9781479970186

harmony search(HS) algorithm is a population-based meta-heuristic algorithm,which is conceptualized using the musical improvisation process of searching for a perfect state of *** this paper,an improved harmony search algorithm with perturbation strategy is proposed to enhance the global and local search ability of HS algorithm.A perturbation strategy is presented to improve global search *** opposition-based learning is used to replace pitch adjustment,which aims to enhance local search *** addition,elite memory is designed to further escape local *** results indicated that the proposed IHSP algorithm has better performance than the state-of-the-art HS algorithms.

关键词： harmony search algorithm Perturbation strategy Opposition-based learning Elite memory

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A Hybrid Approach for Data Clustering using Expectation-Maximization and Parameter Adaptive harmony search algorithm

A Hybrid Approach for Data Clustering using Expectation-Maxi...

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2015 International Conference on Future Computational Technologies (ICFCT’2015);International Conference on Advances in Chemical, Biological & Environmental Engineering (ACBEE);International Conference on Urban Planning, Transport and Construction Engineering (ICUPTCE’15)

作者： Vijay Kumar Jitender Kumar Chhabra Dinesh Kumar Computer Engineering Department National Institute of TechnologyKurukshetraIndia

This paper presents a novel hybrid data clustering algorithm based on parameter adaptive harmony search *** recently developed parameter adaptive harmony search algorithm(PAHS) is used to refine the cluster centers,which are further used in initializing Expectation-Maximization clustering *** optimal number of clusters are determined through four well-known cluster validity *** proposed algorithm is evaluated on three real life datasets and compared with the performance of K-Means,Fuzzy CMeans and HS initialize EM(HSEM).Experimental results reveal that the proposed approach provide better results in terms of precision,recall,weighted average,F-Measure and G-Measure.

关键词： harmony search algorithm Clustering Expectation-Maximization

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Application of harmony search Optimization algorithm to Improve Connectivity in Wireless Sensor Network with Non-uniform Density

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2015年第4期31卷 1475-1489页

作者： Alsaadi, Ali Shanon Wan, Tat-Chee Munther, Alhamza Univ Louisville Comp Engn & Comp Sci Dept Louisville KY 40292 USA Univ Sains Malaysia Sch Comp Sci George Town 11800 Malaysia Univ Malaysia Perlis Sch Comp & Commun Engn Perlis 02600 Malaysia

Low connectivity is a challenging problem in wireless communication sensor networks with non-uniform sensor node densities. Reliable information transmission requires the full connectivity of the network because of the multi-hop communication of wireless sensor networks. A network is fully connected if each pair of nodes can communicate with each other, either directly or through intermediate relay nodes. The current study presents a harmony search (HS) algorithm to improve the connectivity of the non-uniform density wireless sensor networks. HS is a meta-heuristic algorithm, which mimics the actions of harmonizing musical instruments, including memory-based, random, and pitch-adjusted play, during improvisation. In the present work, HS is used to optimize the phase shift parameters of sensors node inside the cluster to ensure maximum radiation field at the reception point. This process results in a significant increase in the coverage area of cluster nodes, consequently increasing network connectivity.

关键词： harmony search algorithm wireless sensor networks connectivity non-uniform density cooperative transmission

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A self-adaptive harmony PSO search algorithm and its performance analysis

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EXPERT SYSTEMS WITH APPLICATIONS 2015年第21期42卷 7436-7455页

作者： Zhao, Fuqing Liu, Yang Zhang, Chuck Wang, Junbiao Lanzhou Univ Technol Sch Comp & Commun Technol Lanzhou 730050 Peoples R China Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Northwestern Polytech Univ Minist Educ Key Lab Contemporary Design & Integrated Mfg Tech Xian 710072 Peoples R China

harmony search (HS) algorithm is a new population-based meta-heuristic which imitates the music improvisation process and has been successfully applied to a variety of combination optimization problems. In this paper, a self-adaptive harmony particle swarm optimization search algorithm, named SHPSOS, is proposed to solve global continuous optimization problems. Firstly, an efficient initialization scheme based on the PSO algorithm is presented for improving the solution quality of the initial harmony memory (HM). Secondly, a new self-adaptive adjusting scheme for pitch adjusting rate (PAR) and distance bandwidth (BW), which can balance fast convergence and large diversity during the improvisation step, are designed. PAR is dynamically adapted by symmetrical sigmoid curve, and BW is dynamically adjusted by the median of the harmony vector at each generation. Meanwhile, a new effective improvisation scheme based on differential evolution and the best harmony (best individual) is developed to accelerate convergence performance and to improve solution accuracy. Besides, Gaussian mutation strategy is presented and embedded in the SHPSOS algorithm to reinforce the robustness and avoid premature convergence in the evolution process of candidates. Finally, the global convergence performance of the SHPSOS is analyzed with the Markov model to testify the stability of algorithm. Experimental results on thirty-two standard benchmark functions demonstrate that SHPSOS outperforms original HS and the other related algorithms in terms of the solution quality and the stability. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： harmony search algorithm PSO algorithm Self-adaptive scheme Mutation strategy Markov model

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A quantum multi-objective optimization algorithm based on harmony search method

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SOFT COMPUTING 2021年第14期25卷 9427-9439页

作者： Sadeghi Hesar, Alireza Kamel, Seyed Reza Houshmand, Mahboobeh Islamic Azad Univ Dept Comp Engn Mashhad Branch Mashhad Razavi Khorasan Iran

The purpose of multi-objective optimization is to simultaneously optimize several objective functions that are usually in conflict with each other. An acceptable solution is one that can strike a trade-off between the results of these functions. Although, multi-objective evolutionary algorithms have a good history in solving multi-objective problems, how to find more accurate and diverse solutions set at an acceptable time is still a challenge. In this study, a quantum-inspired multi-objective harmony search algorithm is proposed to solve multi-objective optimization problems. In this algorithm, a new quantum mutation strategy is proposed, which is a combination of harmony improvisation operators and a quantum adaptive rotation gate. While the use of the rotation gate leads to the move to further solutions and complete coverage of the problem space, the improvisation operators (PAR and BW) trigger tiny impulses and mutate into neighbor solutions. The advantage of such an algorithm is to strengthen the balance between the exploration and exploitation processes. Also, the crowding distance metric of the elitism strategy ensures the production of solutions with maximum variety in the problem space. The results of the implementation of this algorithm on multi-objective benchmark functions indicate significant improvement in criteria such as the distance to Pareto optimal, the scattering, and the convergence rate compared to the state-of-the-art methods.

关键词： Multi-objective optimization Pareto dominance Quantum evolutionary algorithms harmony search algorithm Elitism

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