Relevant bibliographies by topics / Improved harmony search

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Improved harmony search'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Improved harmony search"

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Ouyang, Hai-bin, Li-qun Gao, Steven Li, Xiang-yong Kong, Qing Wang, and De-xuan Zou. "Improved Harmony Search Algorithm: LHS." Applied Soft Computing 53 (April 2017): 133–67. http://dx.doi.org/10.1016/j.asoc.2016.12.042.

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Li, Jian Ping, Ai Ping Lu, Hao Chang Wang, Xin Li, and Pan Chi Li. "An Improved Harmony Search Algorithm with Application." Applied Mechanics and Materials 687-691 (November 2014): 1367–72. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1367.

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In classical harmony search algorithm, only one harmony vector is obtained in each of iteration, which affects its search ability. We propose an improve harmony search algorithm in this paper. In our approach, the number of harmony vectors obtained in each of iteration is equivalent to the population size, and all newly generated harmony vectors are put into the harmony memory array. Then, all harmony vectors are sorted by descending order of the fitness, and the first half individuals are served as the next generation of populations. Experimental results show that our approach is obviously su
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Kang, Di-Wen, Li-Ping Mo, and Kai-Qing Zhou. "An Improved Harmony Search Algorithm with Segmented Search." IOP Conference Series: Materials Science and Engineering 864 (July 10, 2020): 012063. http://dx.doi.org/10.1088/1757-899x/864/1/012063.

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Kong, Zhi, Guo Dong Zhang, and Li Fu Wang. "An Improved Novel Global Harmony Search Algorithm." Applied Mechanics and Materials 644-650 (September 2014): 2169–72. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2169.

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This paper develops an improved novel global harmony search (INGHS) algorithm for solving optimization problems. INGHS employs a novel method for generating new solution vectors that enhances accuracy and convergence rate of novel global harmony search (NGHS) algorithm. Simulations for five benchmark test functions show that INGHS possesses better ability to find the global optimum than that of harmony search (HS) algorithm. Compared with NGHS and HS, INGHS is better in terms of robustness and efficiency.
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Ajay Kumar Beesetti, Ajay Kumar Beesetti. "Automatic Clustering Using Improved Harmony Search." IOSR Journal of Computer Engineering 9, no. 5 (2013): 65–68. http://dx.doi.org/10.9790/0661-0956568.

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Zhang, Ping, Mei Ling Li, Qian Han, Yi Ning Zhang, and Guo Jun Li. "Improved Global Harmony Search Algorithm for Numerical Optimization." Applied Mechanics and Materials 587-589 (July 2014): 2295–98. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.2295.

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To intend to improve the optimization performance of harmony search (HS) algorithm, an improved global harmony search (IGHS) algorithm was presented in this paper. In this algorithm, inspired by swarm intelligence, the global best harmony are borrowed to enhance the optimization accuracy of HS; and mutation and crossover operation instead of pitch adjustment operation to improved the algorithm convergence rate. The key parameters are adjusted to balance the local and global search. Several benchmark experiment simulations, the IGHS has demonstrated stronger convergence and stability than origi
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Xia, Hong Gang, and Qing Liang Wang. "Improved Harmony Search Algorithm with Crossover Operation." Applied Mechanics and Materials 415 (September 2013): 353–56. http://dx.doi.org/10.4028/www.scientific.net/amm.415.353.

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Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method and it does depend on imitating the music improvisation process to generate a perfect state of harmony. However, intelligent optimization methods is easily trapped into local optimal, HS is no exception. In order to improve the performance of HS, a new variant of harmony search algorithm is proposed in this paper. The variant introduce a new crossover operation into HS, and design a strategy to adjust parameter pitch adjusting rate (PAR) and bandwidth (BW). Several standard benchmarks carried out to be teste
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Xia, Hong Gang, Qing Zhou Wang, and Li Qun Gao. "Opposition-Based Improved Harmony Search Algorithm Solve Unconstrained Optimization Problems." Applied Mechanics and Materials 365-366 (August 2013): 170–73. http://dx.doi.org/10.4028/www.scientific.net/amm.365-366.170.

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This paper develops an opposition-based improved harmony search algorithm (OIHS) for solving global continuous optimization problems. The proposed method is different from the classical harmony search (HS) in three aspects. Firstly, the candidate harmony is randomly chosen from the harmony memory or opposition harmony memory was generated by opposition-based learning, which enlarged the algorithm search space. Secondly, two key control parameters, pitch adjustment rate (PAR) and bandwidth distance (bw), are adjusted dynamically with respect to the evolution of the search process. Numerical res
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Li, Hui, Po-Chou Shih, Xizhao Zhou, Chunming Ye, and Li Huang. "An Improved Novel Global Harmony Search Algorithm Based on Selective Acceptance." Applied Sciences 10, no. 6 (2020): 1910. http://dx.doi.org/10.3390/app10061910.

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The novel global harmony search (NGHS) algorithm is proposed in 2010, and it is an improved harmony search (HS) algorithm which combines the particle swarm optimization (PSO) and the genetic algorithm (GA). One of the main differences between the HS and NGHS algorithms is that of using different mechanisms to renew the harmony memory (HM). In the HS algorithm, in each iteration, the new harmony is accepted and replaced the worst harmony in the HM while the fitness of the new harmony is better than the worst harmony in the HM. Conversely, in the NGHS algorithm, the new harmony replaces the wors
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Wang, Ling, Ruixin Yang, Yin Xu, Qun Niu, Panos M. Pardalos, and Minrui Fei. "An improved adaptive binary Harmony Search algorithm." Information Sciences 232 (May 2013): 58–87. http://dx.doi.org/10.1016/j.ins.2012.12.043.

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Dissertations / Theses on the topic "Improved harmony search"

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Liou, Yu-Jhe, and 劉宇哲. "An Improved Harmony Search Algorithm for Structural Optimization." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/25907647736599672577.

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碩士<br>淡江大學<br>航空太空工程學系碩士班<br>103<br>The Harmony Search (HS) Algorithm is conceptualized by using the musical process of searching for a perfect state of harmony. The HS algorithm does not required the setting of initial values of decision variables and was used stochastic random search. In addition, the HS algorithm is simple in concept, few parameters needed, and easy implementation. The Improved Harmony Search (IHS) Algorithm for structural optimization is developed in this study. IHS employs a novel method that enhances accuracy and search capability of harmony search (HS) algorithm. The ha
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Book chapters on the topic "Improved harmony search"

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Geem, Zong Woo. "Improved Harmony Search from Ensemble of Music Players." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11892960_11.

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Anusuman, S. K., and Philomina Simon. "Improved Edge-Preserving Decomposition Based on Single Image Dehazing." In Harmony Search and Nature Inspired Optimization Algorithms. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0761-4_43.

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Dangi, Ramraj, and Satish Pawar. "An Improved Authentication and Data Security Approach Over Cloud Environment." In Harmony Search and Nature Inspired Optimization Algorithms. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0761-4_100.

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Kaur, Jatinder, Surjeet Singh Chauhan, and Pavitdeep Singh. "An Improved TLBO Leveraging Group and Experience Learning Concepts for Global Functions." In Harmony Search and Nature Inspired Optimization Algorithms. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0761-4_113.

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Jiang, Hua, Liping Zheng, and Yanxiu Liu. "Independent Task Scheduling Based on Improved Harmony Search Algorithm." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31020-1_44.

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Zhang, Yang, Jiacheng Li, and Lei Li. "An Improved Clustering-Based Harmony Search Algorithm (IC-HS)." In Lecture Notes in Networks and Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82196-8_9.

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Sethi, Neha, Surjit Singh, and Gurvinder Singh. "Improved Mutation-Based Particle Swarm Optimization for Load Balancing in Cloud Data Centers." In Harmony Search and Nature Inspired Optimization Algorithms. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0761-4_88.

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Hu, Ting-dong. "Improved Harmony Search Algorithm in Strip Mine Vehicle Route Research." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27287-5_90.

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Song, Guangwei, Hongfei Yu, Ben Niu, and Li Li. "An Improved Harmony Search Algorithms Based on Particle Swarm Optimizer." In Intelligent Computing Theories and Technology. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39482-9_70.

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Yu, Jian, and Ping Guo. "Improved PSO Algorithm with Harmony Search for Complicated Function Optimization Problems." In Advances in Neural Networks – ISNN 2012. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31346-2_70.

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Conference papers on the topic "Improved harmony search"

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Kong, Zhi, Lifu Wang, Zhaoxia Wu, Shiqing Qi, and Dexuan Zou. "An improved adaptive harmony search algorithm." In 2012 10th World Congress on Intelligent Control and Automation (WCICA 2012). IEEE, 2012. http://dx.doi.org/10.1109/wcica.2012.6357976.

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Li-min, Zhang. "An Improved Adaptive Harmony Search Algorithm." In 2015 International Conference on Computational Science and Engineering. Atlantis Press, 2015. http://dx.doi.org/10.2991/iccse-15.2015.11.

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Zhang, Ping, Haibin Ouyang, and Liqun Gao. "Improved harmony search algorithm with perturbation strategy." In 2015 27th Chinese Control and Decision Conference (CCDC). IEEE, 2015. http://dx.doi.org/10.1109/ccdc.2015.7162873.

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Zhang, Ting, Bin Jiao, Hai Liu, and Long Peng. "An Improved Harmony Search Algorithm a Application." In 5th International Conference on Information Engineering for Mechanics and Materials. Atlantis Press, 2015. http://dx.doi.org/10.2991/icimm-15.2015.39.

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Li, Guojun, and Hongyu Wang. "Improved harmony search algorithm for global optimization." In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407251.

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Pandi, V. Ravikumar, B. K. Panigrahi, Manas Kumar Mallick, Ajith Abraham, and Swagatam Das. "Improved Harmony Search for Economic Power Dispatch." In 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/his.2009.294.

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Geethanjali, S., and S. Shanmugapriya. "Improved harmony search algorithm for economic emission dispatch." In 2014 IEEE 2nd International Conference on Electrical Energy Systems (ICEES). IEEE, 2014. http://dx.doi.org/10.1109/icees.2014.6924132.

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Shih-Pang Tseng. "An improved harmony search for travelling salesman problem." In 2016 2nd IEEE International Conference on Computer and Communications (ICCC). IEEE, 2016. http://dx.doi.org/10.1109/compcomm.2016.7924712.

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Zhu, Qidan, and Yong Li. "Improved Harmony search Algorithm for Bus Scheduling Optimization." In 2019 Chinese Control And Decision Conference (CCDC). IEEE, 2019. http://dx.doi.org/10.1109/ccdc.2019.8833170.

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Li, Gang, Qingzhong Wang, and Quan Du. "Improved harmony search algorithms by tournament selection operator." In 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015. http://dx.doi.org/10.1109/cec.2015.7257278.

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Journal articles
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