{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:42:29Z","timestamp":1761896549882,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2017,4,28]],"date-time":"2017-04-28T00:00:00Z","timestamp":1493337600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Liaoning Provincial Department of Education Science Foundation","award":["L2013064"],"award-info":[{"award-number":["L2013064"]}]},{"name":"AVIC Technology Innovation Fund (basic research)","award":["2013S60109R"],"award-info":[{"award-number":["2013S60109R"]}]},{"name":"Research Project of Education Department of Liaoning Province","award":["L201630"],"award-info":[{"award-number":["L201630"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The Dynamic Search Fireworks Algorithm (dynFWA) is an effective algorithm for solving optimization problems. However, dynFWA easily falls into local optimal solutions prematurely and it also has a slow convergence rate. In order to improve these problems, an adaptive mutation dynamic search fireworks algorithm (AMdynFWA) is introduced in this paper. The proposed algorithm applies the Gaussian mutation or the Levy mutation for the core firework (CF) with mutation probability. Our simulation compares the proposed algorithm with the FWA-Based algorithms and other swarm intelligence algorithms. The results show that the proposed algorithm achieves better overall performance on the standard test functions.<\/jats:p>","DOI":"10.3390\/a10020048","type":"journal-article","created":{"date-parts":[[2017,4,28]],"date-time":"2017-04-28T11:57:04Z","timestamp":1493380624000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Adaptive Mutation Dynamic Search Fireworks Algorithm"],"prefix":"10.3390","volume":"10","author":[{"given":"Xi-Guang","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer, Shenyang Aerospace University, Shenyang 110136, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3583-7735","authenticated-orcid":false,"given":"Shou-Fei","family":"Han","sequence":"additional","affiliation":[{"name":"School of Computer, Shenyang Aerospace University, Shenyang 110136, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer, Shenyang Aerospace University, Shenyang 110136, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang-Qing","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Computer, Shenyang Aerospace University, Shenyang 110136, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Jing","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer, Shenyang Aerospace University, Shenyang 110136, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Tan, Y., and Zhu, Y. (2010). Fireworks Algorithm for Optimization. Advances in Swarm Intelligence, Proceedings of the 2010 International Conference in Swarm Intelligence, Beijing, China, 12\u201315 June 2010, Springer.","DOI":"10.1007\/978-3-642-13498-2"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zheng, S., Janecek, A., and Tan, Y. (2013, January 20\u201323). Enhanced fireworks algorithm. Proceedings of the 2013 IEEE Congress on Evolutionary Computation, Cancun, Mexico.","DOI":"10.1109\/CEC.2013.6557813"},{"key":"ref_3","unstructured":"Zheng, S., Li, J., and Tan, Y. (2014, January 6\u201311). Adaptive fireworks algorithm. Proceedings of the 2014 IEEE Congress on Evolutionary Computation, Beijing, China."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zheng, S., and Tan, Y. (2014, January 6\u201311). Dynamic search in fireworks algorithm. Proceedings of the 2014 IEEE Congress on Evolutionary Computation, Beijing, China.","DOI":"10.1109\/CEC.2014.6900485"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"26","DOI":"10.3390\/a10010026","article-title":"Analysis and Improvement of Fireworks Algorithm","volume":"10","author":"Li","year":"2017","journal-title":"Algorithms"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Tan, Y. (2015). Fireworks Algorithm Introduction, Science Press. [1st ed.]. (In Chinese).","DOI":"10.1007\/978-3-662-46353-6_1"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1504\/IJMIC.2011.043157","article-title":"Cultural firework algorithm and its application for digital filters design","volume":"4","author":"Gao","year":"2011","journal-title":"Int. J. Model. Identif. Control"},{"key":"ref_8","unstructured":"Andreas, J., and Tan, Y. (2011). Using population based algorithms for initializing nonnegative matrix factorization. Advances in Swarm Intelligence, Proceedings of the 2010 International Conference in Swarm Intelligence, Chongqing, China, 12\u201315 June 2011, Springer."},{"key":"ref_9","unstructured":"Wen, R., Mi, G.Y., and Tan, Y. (2013, January 12\u201315). Parameter optimization of local-concentration model for spam detection by using fireworks algorithm. Proceedings of the 4th International Conference on Swarm Intelligence, Harbin, China."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zheng, S., and Tan, Y. (2013, January 23\u201325). A unified distance measure scheme for orientation coding in identification. Proceedings of the 2013 IEEE Congress on Information Science and Technology, Yangzhou, China.","DOI":"10.1109\/ICIST.2013.6747701"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.advengsoft.2014.04.005","article-title":"Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints","volume":"75","author":"Pholdee","year":"2014","journal-title":"Adv. Eng. Softw."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yang, X., and Tan, Y. (2014). Sample index based encoding for clustering using evolutionary computation. Advances in Swarm Intelligence, Proceedings of the 2014 International Conference on Swarm Intelligence, Hefei, China, 17\u201320 October 2014, Springer.","DOI":"10.1007\/978-3-319-11857-4_55"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.ijepes.2014.04.034","article-title":"A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using fireworks algorithm","volume":"62","author":"Kowsalya","year":"2014","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_14","first-page":"121","article-title":"Evolutionary Programming Using Mutations Based on the t Probability Distribution","volume":"36","author":"Zhou","year":"2008","journal-title":"Acta Electron. Sin."},{"key":"ref_15","first-page":"146","article-title":"Improved Artificial Fish Swarm Algorithm Mixing Levy Mutation and Chaotic Mutation","volume":"42","author":"Fei","year":"2016","journal-title":"Comput. Eng."},{"key":"ref_16","unstructured":"Liang, J., Qu, B., Suganthan, P., and Hernandez-Diaz, A.G. (2013). Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session on Real-Parameter Optimization, Zhengzhou University. Technical Report 201212."},{"key":"ref_17","unstructured":"Teng, S.Z., and Feng, J.H. (2005). Mathematical Statistics, Dalian University of Technology Press. [4th ed.]. (In Chinese)."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","article-title":"A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm","volume":"39","author":"Karaboga","year":"2007","journal-title":"J. Glob. Optim."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zambrano-Bigiarini, M., Clerc, M., and Rojas, R. (2013, January 20\u201323). Standard particle swarm optimization 2011 at CEC2013: A baseline for future PSO improvements. Proceedings of the 2013 IEEE Congress on Evolutionary Computation, Cancun, Mexico.","DOI":"10.1109\/CEC.2013.6557848"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution\u2014A simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"J. Glob. Optim."},{"key":"ref_21","unstructured":"Hansen, N., and Ostermeier, A. (1996, January 20\u201322). Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation. Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, Nagoya, Japan."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/10\/2\/48\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:34:05Z","timestamp":1760207645000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/10\/2\/48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4,28]]},"references-count":21,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2017,6]]}},"alternative-id":["a10020048"],"URL":"https:\/\/doi.org\/10.3390\/a10020048","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2017,4,28]]}}}