{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T05:19:42Z","timestamp":1772860782821,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,11,14]],"date-time":"2019-11-14T00:00:00Z","timestamp":1573689600000},"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>For solving the complex flexible job-shop scheduling problem, an improved genetic algorithm with adaptive variable neighborhood search (IGA-AVNS) is proposed. The improved genetic algorithm first uses a hybrid method combining operation sequence (OS) random selection with machine assignment (MA) hybrid method selection to generate the initial population, and it then groups the population. Each group uses an improved genetic operation for global search, then the better solutions from each group are stored in the elite library, and finally, the adaptive local neighborhood search is used in the elite library for detailed local searches. The simulation experiments are carried out by three sets of international standard examples. The experimental results show that the IGA-AVNS algorithm is an effective algorithm for solving flexible job-shop scheduling problems.<\/jats:p>","DOI":"10.3390\/a12110243","type":"journal-article","created":{"date-parts":[[2019,11,14]],"date-time":"2019-11-14T10:56:34Z","timestamp":1573728994000},"page":"243","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["An Improved Genetic Algorithm with Adaptive Variable Neighborhood Search for FJSP"],"prefix":"10.3390","volume":"12","author":[{"given":"Xiaolin","family":"Gu","sequence":"first","affiliation":[{"name":"Software Technology Institute, Dalian Jiaotong University, Dalian 116021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Huang","sequence":"additional","affiliation":[{"name":"Software Technology Institute, Dalian Jiaotong University, Dalian 116021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Liang","sequence":"additional","affiliation":[{"name":"Software Technology Institute, Dalian Jiaotong University, Dalian 116021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1186\/s40064-016-3054-z","article-title":"Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization","volume":"5","author":"Huang","year":"2016","journal-title":"SpringerPlus"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"13","DOI":"10.2174\/1874110X01610010013","article-title":"A Novel Hybrid Method for Solving Flexible Job-Shop Scheduling Problem","volume":"10","author":"Ning","year":"2016","journal-title":"Open Cybern. 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