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Conference Paper: Stochastic Lot Sizing for Shareholder Wealth Maximisation under Carbon Footprint Management

TitleStochastic Lot Sizing for Shareholder Wealth Maximisation under Carbon Footprint Management
Authors
KeywordsCarbon emission
Stochastic programming
Shareholder wealth
Lot sizing
Make-to-order
Issue Date2015
PublisherEngineering and Technology Publishing. The Journal's web site is located at http://www.jiii.org/
Citation
International Conference on Industrial Engineering and Applications (ICIEA 2014), Sydney, Australia, 29-30 May 2014. In Journal of Industrial and Intelligent Information, 2015, v. 3 n. 1, p. 1-8 How to Cite?
AbstractThere is a growing consensus that human beings must cut greenhouse gas emissions to mitigate global warming and the resultant impacts on the environment. However, production optimisation has rarely taken this issue into consideration, often leading to environmentally unsustainable operation decisions. This paper presents a lot sizing batch optimisation model for a stochastic make-to-order production environment under the carbon emission trading mechanism—currently the most effective market-based carbon emission controlling system, with an aim to maximise the long-term sustainable interests of corporate owners, well-known as the shareholder wealth. To more closely reflect the real-world manufacturing environment, the proposed model adopts general distributions, instead of unrealistic theoretical assumptions, for random variables. We apply the model to investigate the impacts of the carbon emission trading mechanism on shareholder wealth, and test its hedging capability against a series of risk factors. The analytical results provide insights into production optimisation with carbon footprint management.
DescriptionFulltext in http://www.jiii.org/index.php?m=content&c=index&a=show&catid=41&id=141
Persistent Identifierhttp://hdl.handle.net/10722/198617
ISSN

 

DC FieldValueLanguage
dc.contributor.authorWang, XJen_US
dc.contributor.authorChoi, SHen_US
dc.date.accessioned2014-07-07T08:13:00Z-
dc.date.available2014-07-07T08:13:00Z-
dc.date.issued2015en_US
dc.identifier.citationInternational Conference on Industrial Engineering and Applications (ICIEA 2014), Sydney, Australia, 29-30 May 2014. In Journal of Industrial and Intelligent Information, 2015, v. 3 n. 1, p. 1-8en_US
dc.identifier.issn2301-3745-
dc.identifier.urihttp://hdl.handle.net/10722/198617-
dc.descriptionFulltext in http://www.jiii.org/index.php?m=content&c=index&a=show&catid=41&id=141-
dc.description.abstractThere is a growing consensus that human beings must cut greenhouse gas emissions to mitigate global warming and the resultant impacts on the environment. However, production optimisation has rarely taken this issue into consideration, often leading to environmentally unsustainable operation decisions. This paper presents a lot sizing batch optimisation model for a stochastic make-to-order production environment under the carbon emission trading mechanism—currently the most effective market-based carbon emission controlling system, with an aim to maximise the long-term sustainable interests of corporate owners, well-known as the shareholder wealth. To more closely reflect the real-world manufacturing environment, the proposed model adopts general distributions, instead of unrealistic theoretical assumptions, for random variables. We apply the model to investigate the impacts of the carbon emission trading mechanism on shareholder wealth, and test its hedging capability against a series of risk factors. The analytical results provide insights into production optimisation with carbon footprint management.en_US
dc.languageengen_US
dc.publisherEngineering and Technology Publishing. The Journal's web site is located at http://www.jiii.org/-
dc.relation.ispartofJournal of Industrial and Intelligent Informationen_US
dc.subjectCarbon emission-
dc.subjectStochastic programming-
dc.subjectShareholder wealth-
dc.subjectLot sizing-
dc.subjectMake-to-order-
dc.titleStochastic Lot Sizing for Shareholder Wealth Maximisation under Carbon Footprint Managementen_US
dc.typeConference_Paperen_US
dc.identifier.emailWang, XJ: kxjwang@hku.hken_US
dc.identifier.emailChoi, SH: shchoi@hkucc.hku.hk-
dc.identifier.authorityChoi, SH=rp00109en_US
dc.identifier.doi10.12720/jiii.3.1.1-8-
dc.identifier.hkuros229969en_US
dc.identifier.hkuros229970-
dc.identifier.volume3-
dc.identifier.issue1-
dc.identifier.spage1-
dc.identifier.epage8-
dc.publisher.placeUnited States-
dc.description.otherInternational Conference on Industrial Engineering and Applications (ICIEA 2014), Sydney, Australia, 29-30 May 2014. In Journal of Industrial and Intelligent Information, 2015, v. 3 n. 1, p. 1-8-
dc.identifier.issnl2301-3745-

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