Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104370
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorTsang, YPen_US
dc.creatorChoy, KLen_US
dc.creatorWu, CHen_US
dc.creatorHo, GTSen_US
dc.creatorLam, HYen_US
dc.creatorTang, Ven_US
dc.date.accessioned2024-02-05T08:48:39Z-
dc.date.available2024-02-05T08:48:39Z-
dc.identifier.issn0956-7135en_US
dc.identifier.urihttp://hdl.handle.net/10397/104370-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Tsang, Y. P., Choy, K. L., Wu, C. H., Ho, G. T. S., Lam, H. Y., & Tang, V. (2018). An intelligent model for assuring food quality in managing a multi-temperature food distribution centre. Food Control, 90, 81–97 is available at https://doi.org/10.1016/j.foodcont.2018.02.030.en_US
dc.subjectGenetic algorithmen_US
dc.subjectInternet of thingsen_US
dc.subjectMulti-temperature food distributionen_US
dc.subjectTaguchi methoden_US
dc.subjectVehicle routing problemen_US
dc.titleAn intelligent model for assuring food quality in managing a multi-temperature food distribution centreen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage81en_US
dc.identifier.epage97en_US
dc.identifier.volume90en_US
dc.identifier.doi10.1016/j.foodcont.2018.02.030en_US
dcterms.abstractIn the globalized cold chain network, the effective distribution of perishable food is of utmost importance when transporting multiple types of food with different handling requirements, such as temperature and humidity, for minimizing the food spoilage rate during transportation. Currently, mismanagement of premium fruit and vegetables leads to a huge amount of capital loss such that logistics service providers (LSPs) apply refrigerated trucks to deliver them for the sake of minimizing the food spoilage rate during transportation. Since different types of food have their own different handling requirements, traditional refrigerated distribution management at a fixed environmental condition is insufficient. Without considering such requirements, traditional route planning by merely minimizing the travelling distance is ineffective in maintaining food quality, resulting in an increased likelihood of food deterioration and food chilling injury. In addition, there is a lack of real-time product monitoring to control violations of the required handling requirements in order to prevent delivery of spoilt food to customers. In this paper, an internet of things (IoT)-based route planning system (IRPS) is proposed (i) to design a multi-temperature packaging model, (ii) to develop real-time product monitoring during transportation, and (iii) to optimize routing solutions. Under the IoT framework, the ambient environmental information can be collected automatically by building a wireless sensor network so as to develop total product monitoring during the distribution process. Experiments using the Taguchi method are conducted to examine the most effective packaging model for various products in terms of maximizing duration of optimal environment conditions in tertiary packaging. By integrating the above results and travelling constraints, the optimal delivery routes can be formulated by using genetic algorithms (GAs). With the aid of IRPS, the food spoilage rate during transportation and the time needed in route planning and in the delivery of deteriorated food can be reduced, while customer satisfaction is enhanced.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationFood control, Aug. 2018, v. 90, p. 81-97en_US
dcterms.isPartOfFood controlen_US
dcterms.issued2018-08-
dc.identifier.scopus2-s2.0-85042647514-
dc.identifier.eissn1873-7129en_US
dc.description.validate202402 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0612-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6823951-
dc.description.oaCategoryGreen (AAM)en_US
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