Advances in Online Delivery: Introducing and Optimizing a Novel Multi-Objective Function

Advances in Online Delivery: Introducing and Optimizing a Novel Multi-Objective Function | 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 Advances in Online Delivery: Introducing and Optimizing a Novel Multi-Objective Function Harinandan Tunga, Rupaj Chowdhury, Samarjit Kar, Debasis Giri, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3631574/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 An efficient online delivery system in the dynamic landscape is a challenging task. The challenges occur due to the difficulty in generating a proper objective function that can represent theperformance of the delivery system. In this paper, we propose a novel multi-objective function that represents the utility score and time required in the delivery process. The utility score takes into consideration the number of previous orders given by a particular customer. The Time window methodology is used to achieve the two objectives. The multi-objective optimization functions are solved and compared using three multi-objective algorithms. They are Non-dominated sorting genetic algorithm-II (NSGA-II), strength Pareto evolutionary algorithm 2 (SPEA2), and indicator-based evolutionary algorithm (IBEA). The performances are compared extensively and it is found that SPEA2 gives better convergence performance. The proposed objective function minimizes the limitation of currently available methods for online delivery systems. Physical sciences/Engineering Physical sciences/Mathematics and computing Orienteering problem Time Window Routing optimization Total utility score Total delivery time Multi-objective evolutionary algorithms 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-3631574","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":252992951,"identity":"60187796-1ed4-4790-a1ae-34ff8fb506ec","order_by":0,"name":"Harinandan Tunga","email":"","orcid":"","institution":"RCC Institute of Information Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Harinandan","middleName":"","lastName":"Tunga","suffix":""},{"id":252992952,"identity":"51fb75df-b05e-4ed4-87fa-b50ea5bad64c","order_by":1,"name":"Rupaj Chowdhury","email":"","orcid":"","institution":"RCC Institute of Information Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rupaj","middleName":"","lastName":"Chowdhury","suffix":""},{"id":252992956,"identity":"cc4c2ff5-864f-4f2c-9e17-c7a85aa4e3aa","order_by":2,"name":"Samarjit Kar","email":"","orcid":"","institution":"National Institute of Technology Durgapur","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Samarjit","middleName":"","lastName":"Kar","suffix":""},{"id":252992959,"identity":"83125aa1-2d8b-468b-b368-82f9bcbaf314","order_by":3,"name":"Debasis Giri","email":"","orcid":"","institution":"Maulana Abul Kalam Azad University of Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Debasis","middleName":"","lastName":"Giri","suffix":""},{"id":252992961,"identity":"d030ba42-be79-4416-ad5b-d42471d52e0e","order_by":4,"name":"Amir H Gandomi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYJACCSCSgzDZSNBiDFFNghaGxAaitci7nz1442OORfqG++0PGD6UHWbgn5GAX4vhmbxky5nbJHI3HOMxYJxx7jCDxA1CWhpyzKR5IVoYmHnbDjMwENTS/wasJd3gGPsD5r9ALfKEtMhLQGxJMDjGYMDMCNRiQEiLgcQbY5BfDGceyzE42HMuncfwzAMCtvTnGN74uK1Onu/w8YcPfpRZy8kdJ2TLASQOiM2DXz3IlgaCSkbBKBgFo2DEAwCrGEISG1GicgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Technology Sydney","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Amir","middleName":"H","lastName":"Gandomi","suffix":""}],"badges":[],"createdAt":"2023-11-18 18:29:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3631574/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3631574/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49369039,"identity":"dba47b14-13d8-4766-adf6-7565cc763f9d","added_by":"auto","created_at":"2024-01-09 13:22:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":631390,"visible":true,"origin":"","legend":"","description":"","filename":"23.11.23AdvancesinOnlineDelivery.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3631574/v1_covered_0a045232-385c-4d36-af1a-bb5a8fc4bfcc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Advances in Online Delivery: Introducing and Optimizing a Novel Multi-Objective Function","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":"Orienteering problem, Time Window, Routing optimization, Total utility score, Total delivery time, Multi-objective evolutionary algorithms","lastPublishedDoi":"10.21203/rs.3.rs-3631574/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3631574/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAn efficient online delivery system in the dynamic landscape is a challenging task. The challenges occur due to the difficulty in generating a proper objective function that can represent theperformance of the delivery system. In this paper, we propose a novel multi-objective function that represents the utility score and time required in the delivery process. The utility score takes into consideration the number of previous orders given by a particular customer. The Time window methodology is used to achieve the two objectives. The multi-objective optimization functions are solved and compared using three multi-objective algorithms. They are Non-dominated sorting genetic algorithm-II (NSGA-II), strength Pareto evolutionary algorithm 2 (SPEA2), and indicator-based evolutionary algorithm (IBEA). The performances are compared extensively and it is found that SPEA2 gives better convergence performance. The proposed objective function minimizes the limitation of currently available methods for online delivery systems.\u003c/p\u003e","manuscriptTitle":"Advances in Online Delivery: Introducing and Optimizing a Novel Multi-Objective Function","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-11-29 06:16:14","doi":"10.21203/rs.3.rs-3631574/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":"bbd4dbad-4734-4604-8c72-614aad866fbe","owner":[],"postedDate":"November 29th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":26714620,"name":"Physical sciences/Engineering"},{"id":26714621,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2024-01-09T13:14:19+00:00","versionOfRecord":[],"versionCreatedAt":"2023-11-29 06:16:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3631574","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3631574","identity":"rs-3631574","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}