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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/11592
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dc.contributor.authorRoutroy, Srikanta-
dc.contributor.authorGarg, Girish Kant-
dc.date.accessioned2023-08-23T08:37:15Z-
dc.date.available2023-08-23T08:37:15Z-
dc.date.issued2021-
dc.identifier.urihttps://www.taylorfrancis.com/chapters/edit/10.1201/9781003055037-8/application-optimization-statistical-techniques-post-harvest-supply-chain-rahul-priyadarshi-srikanta-routroy-girish-kant-garg-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11592-
dc.description.abstractThe objective of this literature survey is to address the utility and potential of optimization, statistical surveys and mathematical research into post-harvest supply chains (PHSCs) to reduce losses. Empirical approaches have always helped to understand a generic issue with a specific perspective to highlight the shortcomings with the existing practice. The optimization approaches are used in the PHSC literature to design an optimum system to enhance revenues and to minimize losses. The existing PHSCs in developing countries such as India suffer enormous losses – e.g., revenue losses, physical damage of produce, microbial losses, qualitative losses, quantitative losses, etc. – in the absence of market prospects due to inefficient packaging for transportation and handling. This study covers a systematic literature survey covering the mathematical, statistical and optimization research performed in the field of PHSC and critical analysis to highlight the key aspects covered in the literature and their future scope.en_US
dc.language.isoenen_US
dc.publisherCRC Pressen_US
dc.subjectMechanical Engineeringen_US
dc.subjectSupply chainen_US
dc.titleApplication of Optimization and Statistical Techniques in Post-Harvest Supply Chainen_US
dc.typeBook chapteren_US
Appears in Collections:Department of Mechanical engineering

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