Improved NSGA-II for the energy-efficient distributed blocking flow shop scheduling problem

Improved NSGA-II for the energy-efficient distributed blocking flow shop scheduling problem | 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 Research Article Improved NSGA-II for the energy-efficient distributed blocking flow shop scheduling problem Haojie Li, Yongquan Zhou, Qifang Luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7434841/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the context of the national carbon peak and carbon neutrality strategies, the green advancement of the manufacturing industry has become a key issue of concern for manufacturing enterprises. This paper takes into account the energy consumption (EC) problem in the Distributed Blocking Flow Shop Scheduling Problem (DBFSP). For the energy-efficient Distributed Blocking Flow Shop Scheduling Problem (EEDBFSP) with the optimization objectives of makespan ( C max ) and total energy consumption (TEC), an improved NSGA-II algorithm (INSGA-II) is presented. The algorithm employs a dual-mode initialization strategy that synergistically combines the improved distributed NEH (IDNEH) heuristic with randomized solution generation, strategically balancing solution quality and population diversity. To strengthen the algorithm's exploration-convergence balance, we design a local search strategy. In addition, by defining the critical path and non-critical path, we accelerate operations on the critical path to optimize the makespan while decelerating those on the non-critical path, which reduces EC without extending the makespan. This paper systematically explores the impact of algorithm parameter settings on the optimization effect and performs extensive comparative experiments with others algorithms. The results of extensive benchmark tests and statistical analyses confirm that INSGA-II, as an optimizer for solving the EEDBFSP, is significantly effective, and its performance is notably better than that of other comparative algorithms. INSGA-II IDNEH heuristic energy-efficient distributed blocking flow shop scheduling problem (EEDBFSP) makespan total energy consumption (TEC) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7434841","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":532260800,"identity":"b6dbb644-5767-460a-98a5-e5a7deff9792","order_by":0,"name":"Haojie Li","email":"","orcid":"","institution":"Guangxi Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Haojie","middleName":"","lastName":"Li","suffix":""},{"id":532260801,"identity":"034d2089-e2dc-457b-90de-5a12bc938d00","order_by":1,"name":"Yongquan 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problem","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"INSGA-II, IDNEH heuristic, energy-efficient distributed blocking flow shop scheduling problem (EEDBFSP), makespan, total energy consumption (TEC)","lastPublishedDoi":"10.21203/rs.3.rs-7434841/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7434841/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the context of the national carbon peak and carbon neutrality strategies, the green advancement of the manufacturing industry has become a key issue of concern for manufacturing enterprises. This paper takes into account the energy consumption (EC) problem in the Distributed Blocking Flow Shop Scheduling Problem (DBFSP). For the energy-efficient Distributed Blocking Flow Shop Scheduling Problem (EEDBFSP) with the optimization objectives of makespan (\u003cem\u003eC\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e) and total energy consumption (TEC), an improved NSGA-II algorithm (INSGA-II) is presented. The algorithm employs a dual-mode initialization strategy that synergistically combines the improved distributed NEH (IDNEH) heuristic with randomized solution generation, strategically balancing solution quality and population diversity. To strengthen the algorithm's exploration-convergence balance, we design a local search strategy. In addition, by defining the critical path and non-critical path, we accelerate operations on the critical path to optimize the makespan while decelerating those on the non-critical path, which reduces EC without extending the makespan. This paper systematically explores the impact of algorithm parameter settings on the optimization effect and performs extensive comparative experiments with others algorithms. The results of extensive benchmark tests and statistical analyses confirm that INSGA-II, as an optimizer for solving the EEDBFSP, is significantly effective, and its performance is notably better than that of other comparative algorithms.\u003c/p\u003e","manuscriptTitle":"Improved NSGA-II for the energy-efficient distributed blocking flow shop scheduling problem","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 23:10:25","doi":"10.21203/rs.3.rs-7434841/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c2158ce4-2628-4052-8a09-5d0d0ac92313","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-04T13:08:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 23:10:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7434841","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7434841","identity":"rs-7434841","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}