Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/433829
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dc.coverage.spatialOptimization study on customer based supply chain network in process industry
dc.date.accessioned2022-12-29T13:10:44Z-
dc.date.available2022-12-29T13:10:44Z-
dc.identifier.urihttp://hdl.handle.net/10603/433829-
dc.description.abstractSupply chain management is a type of management which deals with the movement and storage of raw materials in the form of finished goods from one point to another. In today s competitive global market place improving inefficiency in supply chain management is becoming more critical and in maintaining market share and profitability. Global supply chain is more complex, fragmented, out-dated and challenging. Another drawback is that supply chain management is slow in manual process. newlineThis study is addressed into two parts 1) Reinforcement learning algorithm 2) Nearest neighbourhood algorithm the nearest neighbourhood algorithm paves the way to find the shortest transportation distance among the province and the reinforcement learning algorithm gives an optimal working plan by reducing the workload, transfer cost and maximum profit. The result of this study serves as a reference for business managers and administrators. newlineThe existing model which is followed by the processing industry has minimum cost reducing factors and it is a complex model which has various divisions and doesn t allow getting more optimal results. To reduce those factors and provide more sustained and stable model that is proposing Reinforcement learning algorithm which can be the future of processing industries and can yield more profit. This model will increase the profit yield by decreasing the cost by customer and also reduce the transportation and the cost of regional centres. newline
dc.format.extentxiv,164p.
dc.languageEnglish
dc.relationp.152-163
dc.rightsuniversity
dc.titleOptimization study on customer based supply chain network in process industry
dc.title.alternative
dc.creator.researcherAnand, T
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering
dc.subject.keywordEngineering Mechanical
dc.subject.keywordchain network
dc.subject.keywordprocess industry
dc.description.note
dc.contributor.guideSudhakarapandian, R and Sakthivel, M
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Mechanical Engineering
dc.date.registered
dc.date.completed2021
dc.date.awarded2021
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Mechanical Engineering

Files in This Item:
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01_title.pdfAttached File100.79 kBAdobe PDFView/Open
02_prelim.pages.pdf1.84 MBAdobe PDFView/Open
03_content.pdf86.43 kBAdobe PDFView/Open
04_abstract.pdf64.83 kBAdobe PDFView/Open
05_chapter 1.pdf248.34 kBAdobe PDFView/Open
06_chapter 2.pdf199.88 kBAdobe PDFView/Open
07_chapter 3.pdf446.11 kBAdobe PDFView/Open
08_annexures.pdf123.16 kBAdobe PDFView/Open
80_recommendation.pdf78.62 kBAdobe PDFView/Open


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