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The fruit fly optimization algorithm was a novel swarm intelligence algorithm. In the standard fruit fly optimization algorithm, it is difficult to solve the high-dimensional nonlinear optimization problem and easy to fall into the local optimum. To overcome the shortcomings of the basic fruit fly optimization algorithm, the immune algorithm self\u2013non-self antigen recognition mechanism and the immune system learn\u2013memory\u2013forgetting knowledge processing mechanism were employed. The improved algorithm was introduced to the structural optimization. Optimization results and comparison with other algorithms show that the stability of improved fruit fly optimization algorithm is apparently improved and the efficiency is obviously remarkable. This study provides a more effective solution to structural optimization problems.<\/jats:p>","DOI":"10.1186\/s40708-020-0102-9","type":"journal-article","created":{"date-parts":[[2020,2,16]],"date-time":"2020-02-16T14:02:24Z","timestamp":1581861744000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Improved fruit fly algorithm on structural optimization"],"prefix":"10.1186","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3642-0782","authenticated-orcid":false,"given":"Yancang","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muxuan","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,2,16]]},"reference":[{"issue":"3\u20134","key":"102_CR1","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1007\/s00521-011-0769-1","volume":"22","author":"SM Lin","year":"2013","unstructured":"Lin SM (2013) Analysis of service satisfaction in web auction logistics service using a combination of Fruit fly optimization algorithm and general regression neural network. 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