{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:50:39Z","timestamp":1760709039277,"version":"build-2065373602"},"reference-count":16,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2016,4,1]],"date-time":"2016-04-01T00:00:00Z","timestamp":1459468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The fireworks algorithm (FA) is a new parallel diffuse optimization algorithm to simulate the fireworks explosion phenomenon, which realizes the balance between global exploration and local searching by means of adjusting the explosion mode of fireworks bombs. By introducing the grouping strategy of the shuffled frog leaping algorithm (SFLA), an improved FA-SFLA hybrid algorithm is put forward, which can effectively make the FA jump out of the local optimum and accelerate the global search ability. The simulation results show that the hybrid algorithm greatly improves the accuracy and convergence velocity for solving the function optimization problems.<\/jats:p>","DOI":"10.3390\/a9020023","type":"journal-article","created":{"date-parts":[[2016,4,1]],"date-time":"2016-04-01T10:31:20Z","timestamp":1459506680000},"page":"23","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["An Improved Fireworks Algorithm Based on Grouping Strategy of the Shuffled Frog Leaping Algorithm to Solve Function Optimization Problems"],"prefix":"10.3390","volume":"9","author":[{"given":"Yu-Feng","family":"Sun","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie-Sheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114044, China"},{"name":"National Financial Security and System Equipment Engineering Research Center, University of Science and Technology Liaoning, Anshan 114044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiang-Di","family":"Song","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,4,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1007\/s00500-013-0984-z","article-title":"An efficient algorithm for high-dimensional function optimization","volume":"17","author":"Ren","year":"2013","journal-title":"Soft Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s11721-011-0065-9","article-title":"Continuous optimization algorithms for tuning real and integer parameters of swarm intelligence algorithms","volume":"6","author":"Yuan","year":"2012","journal-title":"Swarm Intell."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4618","DOI":"10.1016\/j.eswa.2011.09.076","article-title":"A survey: Ant colony optimization based recent research and implementation on several engineering domain","volume":"39","author":"Baskaran","year":"2012","journal-title":"Expert Syst. 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