{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T21:37:59Z","timestamp":1775857079141,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T00:00:00Z","timestamp":1723852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In optimization problems, the principle of symmetry provides important guidance. This article introduces an enhanced NSGA-II algorithm, termed NDE-NSGA-II, designed for addressing multi-objective optimization problems. The approach employs Tent mapping for population initialization, thereby augmenting its search capability. During the offspring generation process, a hybrid local search strategy is implemented to augment the population\u2019s exploration capabilities. It is crucial to highlight that in elite selection, norm selection and average distance elimination strategies are adopted to strengthen the selection mechanism of the population. This not only enhances diversity but also ensures convergence, thereby improving overall performance. The effectiveness of the proposed NDE-NSGA-II is comprehensively evaluated across various benchmark functions with distinct true Pareto frontier shapes. The results consistently demonstrate that the NDE-NSGA-II method presented in this paper surpasses the performance metrics of the other five methods. Lastly, the algorithm is integrated with the DSSAT model to optimize maize irrigation and fertilization scheduling, confirming the effectiveness of the improved algorithm.<\/jats:p>","DOI":"10.3390\/sym16081062","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T03:43:28Z","timestamp":1724039008000},"page":"1062","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Enhancing NSGA-II Algorithm through Hybrid Strategy for Optimizing Maize Water and Fertilizer Irrigation Simulation"],"prefix":"10.3390","volume":"16","author":[{"given":"Jinyang","family":"Du","sequence":"first","affiliation":[{"name":"Department of Mathematics, Changchun Normal University, Changchun 130032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1263-041X","authenticated-orcid":false,"given":"Renyun","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Changchun Normal University, Changchun 130032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Du","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Jilin University, Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Changchun Normal University, Changchun 130032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Changchun Normal University, Changchun 130032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fanhua","family":"Yu","sequence":"additional","affiliation":[{"name":"Jilin Communications Polytechnic, Changchun 130015, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.ins.2015.05.026","article-title":"Differential evolution with hybrid linkage crossover","volume":"320","author":"Cai","year":"2015","journal-title":"Inf. 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