Multi-objective optimization of decoration engineering construction organization based on genetic algorithm

Multi-objective optimization of decoration engineering construction organization based on genetic algorithm | 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 Multi-objective optimization of decoration engineering construction organization based on genetic algorithm Shujuan Yang, Dehu Yu, Yu Liu, Baodi Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3871881/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 Abstract：The comprehensive optimization of decoration construction organization is of great significance to rational construction and reduces the construction period and construction costs. Flow construction is an important approach for the optimization of construction decoration engineering; however, it has not been used in the multi-objective optimization of the construction organization in decoration engineering. Moreover, current researches on the multi-objective optimization of the construction organization in decoration engineering does not consider the dynamic situations in practice. Consequently, there exists a difference between optimization research and practice. Therefore, this paper presented a multi-population genetic algorithm (MPGA) for optimizing the construction sequence of orders placed by customers and realizing multi-objective optimization of the construction period, transportation costs, and delay time of decoration engineering. Furthermore, three dynamic scenarios were proposed, where in a new customer placed an order, a process delay occurred, and an emergency order was received; a dynamic multi-objective optimization algorithm was also designed to solve the target problem. The results of the case study revealed that the Pareto solution obtained by the MPGA could shorten the construction period, reduce transportation costs, and reduce labor delay times, as compared with those before optimization. Moreover, the MPGA could effectively solve the multi-objective optimization problem of a decoration engineering construction organization, serving as a reference for the development of algorithms to solve the construction management problem; this, in turn, can promote the reform and development of the construction industry in the intelligent era. Physical sciences/Engineering Physical sciences/Engineering/Civil engineering Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 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-3871881","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":269724111,"identity":"87a45bea-f4c9-4623-8edc-65c0dc3fe0fa","order_by":0,"name":"Shujuan Yang","email":"","orcid":"","institution":"Qingdao University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Shujuan","middleName":"","lastName":"Yang","suffix":""},{"id":269724112,"identity":"b612a113-5732-4620-a05f-8697240d8def","order_by":1,"name":"Dehu 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Flow construction is an important approach for the optimization of construction decoration engineering; however, it has not been used in the multi-objective optimization of the construction organization in decoration engineering. Moreover, current researches on the multi-objective optimization of the construction organization in decoration engineering does not consider the dynamic situations in practice. Consequently, there exists a difference between optimization research and practice. Therefore, this paper presented a multi-population genetic algorithm (MPGA) for optimizing the construction sequence of orders placed by customers and realizing multi-objective optimization of the construction period, transportation costs, and delay time of decoration engineering. Furthermore, three dynamic scenarios were proposed, where in a new customer placed an order, a process delay occurred, and an emergency order was received; a dynamic multi-objective optimization algorithm was also designed to solve the target problem. The results of the case study revealed that the Pareto solution obtained by the MPGA could shorten the construction period, reduce transportation costs, and reduce labor delay times, as compared with those before optimization. Moreover, the MPGA could effectively solve the multi-objective optimization problem of a decoration engineering construction organization, serving as a reference for the development of algorithms to solve the construction management problem; this, in turn, can promote the reform and development of the construction industry in the intelligent era.","manuscriptTitle":"Multi-objective optimization of decoration engineering construction organization based on genetic algorithm","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-30 17:21:09","doi":"10.21203/rs.3.rs-3871881/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":"cf1b3870-18fb-4e50-9e0f-085ca8e82a47","owner":[],"postedDate":"January 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28412749,"name":"Physical sciences/Engineering"},{"id":28412750,"name":"Physical sciences/Engineering/Civil engineering"}],"tags":[],"updatedAt":"2024-03-08T12:23:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-30 17:21:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3871881","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3871881","identity":"rs-3871881","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}