View in EDS HTML Full Text PDF Full Text

Production optimisation in carbon reduction engineering management.

Saved in:
Bibliographic Details
Title: Production optimisation in carbon reduction engineering management.
Authors: Wei, Yi-Ming1 (AUTHOR), Huang, Zhimin2 (AUTHOR), Coffman Dalton, D'Maris3 (AUTHOR), Liao, Hua1 (AUTHOR), Wang, Ke1 (AUTHOR) wangke03@yeah.net
Source: International Journal of Production Research. Sep2024, Vol. 62 Issue 18, p6445-6448. 4p.
Subjects: Deep reinforcement learning, Reinforcement learning, Sustainability, Greenhouse gases, Flow shop scheduling, Supply chain management, Process optimization, Environmental literacy
Abstract: This document discusses the importance of carbon reduction engineering in combating global climate change. It highlights the role of production and supply chain management in achieving carbon neutrality and reducing carbon emissions. The document presents 20 selected research papers that cover various aspects of production optimization in carbon reduction engineering, including carbon reduction in the production process, low-carbon and sustainable supply chains, assessment and optimization methodologies, and policy instruments. The papers provide insights into topics such as scheduling optimization, renewable energy production, carbon emission efficiency, sustainable consumption, government subsidizing arrangements, and the impact of policy instruments on carbon reduction. The document expresses gratitude to the authors and reviewers for their contributions and acknowledges the support of the International Journal of Production Research. [Extracted from the article]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 178681459
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Production optimisation in carbon reduction engineering management.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wei%2C+Yi-Ming%22">Wei, Yi-Ming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Zhimin%22">Huang, Zhimin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Coffman+Dalton%2C+D'Maris%22">Coffman Dalton, D'Maris</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liao%2C+Hua%22">Liao, Hua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Ke%22">Wang, Ke</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wangke03@yeah.net</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Sep2024, Vol. 62 Issue 18, p6445-6448. 4p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Deep+reinforcement+learning%22">Deep reinforcement learning</searchLink><br /><searchLink fieldCode="DE" term="%22Reinforcement+learning%22">Reinforcement learning</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br /><searchLink fieldCode="DE" term="%22Greenhouse+gases%22">Greenhouse gases</searchLink><br /><searchLink fieldCode="DE" term="%22Flow+shop+scheduling%22">Flow shop scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+chain+management%22">Supply chain management</searchLink><br /><searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+literacy%22">Environmental literacy</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This document discusses the importance of carbon reduction engineering in combating global climate change. It highlights the role of production and supply chain management in achieving carbon neutrality and reducing carbon emissions. The document presents 20 selected research papers that cover various aspects of production optimization in carbon reduction engineering, including carbon reduction in the production process, low-carbon and sustainable supply chains, assessment and optimization methodologies, and policy instruments. The papers provide insights into topics such as scheduling optimization, renewable energy production, carbon emission efficiency, sustainable consumption, government subsidizing arrangements, and the impact of policy instruments on carbon reduction. The document expresses gratitude to the authors and reviewers for their contributions and acknowledges the support of the International Journal of Production Research. [Extracted from the article]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=178681459
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2024.2353429
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 4
        StartPage: 6445
    Subjects:
      – SubjectFull: Deep reinforcement learning
        Type: general
      – SubjectFull: Reinforcement learning
        Type: general
      – SubjectFull: Sustainability
        Type: general
      – SubjectFull: Greenhouse gases
        Type: general
      – SubjectFull: Flow shop scheduling
        Type: general
      – SubjectFull: Supply chain management
        Type: general
      – SubjectFull: Process optimization
        Type: general
      – SubjectFull: Environmental literacy
        Type: general
    Titles:
      – TitleFull: Production optimisation in carbon reduction engineering management.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wei, Yi-Ming
      – PersonEntity:
          Name:
            NameFull: Huang, Zhimin
      – PersonEntity:
          Name:
            NameFull: Coffman Dalton, D'Maris
      – PersonEntity:
          Name:
            NameFull: Liao, Hua
      – PersonEntity:
          Name:
            NameFull: Wang, Ke
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 09
              Text: Sep2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 00207543
          Numbering:
            – Type: volume
              Value: 62
            – Type: issue
              Value: 18
          Titles:
            – TitleFull: International Journal of Production Research
              Type: main
ResultId 1