Study on reservoir optimal operation based on coupled adap-tive ε constraint and multi strategy improved Pelican algo-rithm

Study on reservoir optimal operation based on coupled adap-tive ε constraint and multi strategy improved Pelican algo-rithm | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Study on reservoir optimal operation based on coupled adap-tive ε constraint and multi strategy improved Pelican algo-rithm Ji He, Xiaoqi Guo, Songlin Wang, Haitao Chen, Fuxin Chai This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2751897/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Aug, 2023 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract The optimal operation of reservoir group is a multi-constrained and high-dimensional optimization problem. For this problem, this paper couples the standard pelican optimization algorithm with the adaptive ε-constraint method, and further improves the algorithm's optimization-seeking perfor-mance through the good point set initialization population, reverse differential evolution and op-timal individual adaptive strategy, and proposes an improved pelican algorithm (ε-IPOA) based on the adaptive ε method. The performance of the algorithm is tested by eight constraint test functions to find the optimal ability and solve the constrained optimization problem, and the results show that the algorithm has a strong ability to find the optimal and stable performance. In this paper, we select Sanmenxia and Xiaolangdi reservoirs as the research objects, establish the maximum peak-cutting model of terrace reservoirs, apply the ε-IPOA algorithm to solve the model, and compare it with the ε-POA and ε-DE algorithms, the results show that the ε-IPOA algorithm is better than other algo-rithms, the peak clipping rate of Huayuankou control point solved by ε-IPOA algorithm reached 44%, and other algorithms do not find effective solutions meeting the constraint conditions. This paper provides a new idea for solving the problem of flood control optimal operation of cascade reservoirs. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Hydrology Earth and environmental sciences/Limnology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Aug, 2023 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Major revision 11 Jul, 2023 Reviews received at journal 27 Jun, 2023 Reviewers agreed at journal 17 Jun, 2023 Reviewers invited by journal 17 Jun, 2023 Editor assigned by journal 17 Jun, 2023 Editor invited by journal 10 Apr, 2023 Submission checks completed at journal 10 Apr, 2023 First submitted to journal 29 Mar, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2751897","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":190471802,"identity":"1497f219-12da-41e8-829c-9e05a004d788","order_by":0,"name":"Ji He","email":"","orcid":"","institution":"School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450011, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ji","middleName":"","lastName":"He","suffix":""},{"id":190471803,"identity":"5cac58f6-471e-4005-aa8e-5979bf960216","order_by":1,"name":"Xiaoqi 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