Optimization of cold chain logistics distribution paths for community buying considering cost and time window: The case of J Center
In recent years, the community group buying market has been developing rapidly, and the group buying categories are mainly fresh food, so one of the keys to the success of the community group buying platform lies in the supply chain logistics, in which the cold chain logistics is the key to guarante...
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Veröffentlicht in: | Managerial and decision economics 2024-12, Vol.45 (8), p.5249-5264 |
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creator | Feng, Qun Hua, Wei Chen, Chuanhao Shi, Xuejun Ma, Junyun |
description | In recent years, the community group buying market has been developing rapidly, and the group buying categories are mainly fresh food, so one of the keys to the success of the community group buying platform lies in the supply chain logistics, in which the cold chain logistics is the key to guarantee the fresh food products for the time and quality. In this paper, on the combing research of the theories and problems of community group purchase, cold chain logistics, and vehicle path planning, in view of the existing problems of cold chain logistics and distribution business in Jinan distribution center of J company's community group purchase, taking into account the actual demand of the grid station and the characteristics of the fresh products to be stored at low temperatures, we constructed the optimization model of the cold chain logistics and distribution path that minimizes the total cost under the demand of the fuzzy time window of the grid station, and designed the distribution area is divided by using K‐means clustering, and then, the distribution path in each sub‐distribution area is optimized and solved by genetic algorithm, and then, the validity of the optimization scheme is verified, the number of distribution trucks used is reduced by two, and the distribution cost is reduced by 12.77%, and optimization measures such as promoting the standardization of warehousing and distribution, and creating a digital and integrated logistics information platform are proposed. |
doi_str_mv | 10.1002/mde.4319 |
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In this paper, on the combing research of the theories and problems of community group purchase, cold chain logistics, and vehicle path planning, in view of the existing problems of cold chain logistics and distribution business in Jinan distribution center of J company's community group purchase, taking into account the actual demand of the grid station and the characteristics of the fresh products to be stored at low temperatures, we constructed the optimization model of the cold chain logistics and distribution path that minimizes the total cost under the demand of the fuzzy time window of the grid station, and designed the distribution area is divided by using K‐means clustering, and then, the distribution path in each sub‐distribution area is optimized and solved by genetic algorithm, and then, the validity of the optimization scheme is verified, the number of distribution trucks used is reduced by two, and the distribution cost is reduced by 12.77%, and optimization measures such as promoting the standardization of warehousing and distribution, and creating a digital and integrated logistics information platform are proposed.</description><subject>Clustering</subject><subject>Cold storage</subject><subject>Community</subject><subject>Community organizations</subject><subject>Distribution costs</subject><subject>Fuzzy logic</subject><subject>Genetic algorithms</subject><subject>Logistics</subject><subject>Optimization</subject><subject>Standardization</subject><subject>Supply</subject><subject>Supply chains</subject><subject>Warehousing</subject><issn>0143-6570</issn><issn>1099-1468</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp10E1LwzAYB_AgCs4p-BECXrx05nVtvMmcb0x2mefSJumWsSYzaRn16hc3XQVPnp4Qfvyf5A_ANUYTjBC5q5WeMIrFCRhhJESC2TQ7BSOEGU2mPEXn4CKELUKIZUyMwPdy35jafBWNcRa6Ckq3U1BuCmPhzq1NaIwMUMXpTdke0b5oNgFWzkdb1601TQfLtjN2HS9sMEr74RwaWFgFY76GB2OVO9zD1UZDWQTdr3qDM20b7S_BWVXsgr76nWPw8TRfzV6SxfL5dfawSCRhWCSUc0ZEIWmqCUZTJiTXmVIs5ZzSknAilRRUZoKlGvEeZhSxkmSl0hSlio7BzZC79-6z1aHJt671Nq7MKSaUZykjKKrbQUnvQvC6yvfe1IXvcozyvuI8Vpz3FUcKB6rjx034gwJTQjGKDxiDZCAHs9Pdv1H5--P8GPkD2UmH_A</recordid><startdate>202412</startdate><enddate>202412</enddate><creator>Feng, Qun</creator><creator>Hua, Wei</creator><creator>Chen, Chuanhao</creator><creator>Shi, Xuejun</creator><creator>Ma, Junyun</creator><general>Wiley Periodicals Inc</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><orcidid>https://orcid.org/0000-0003-1442-9695</orcidid></search><sort><creationdate>202412</creationdate><title>Optimization of cold chain logistics distribution paths for community buying considering cost and time window: The case of J Center</title><author>Feng, Qun ; Hua, Wei ; Chen, Chuanhao ; Shi, Xuejun ; Ma, Junyun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2419-355429ac37e210649c5e8dd475533b252cdc93c8947e059ac38304b28bde307d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Clustering</topic><topic>Cold storage</topic><topic>Community</topic><topic>Community organizations</topic><topic>Distribution costs</topic><topic>Fuzzy logic</topic><topic>Genetic algorithms</topic><topic>Logistics</topic><topic>Optimization</topic><topic>Standardization</topic><topic>Supply</topic><topic>Supply chains</topic><topic>Warehousing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Feng, Qun</creatorcontrib><creatorcontrib>Hua, Wei</creatorcontrib><creatorcontrib>Chen, Chuanhao</creatorcontrib><creatorcontrib>Shi, Xuejun</creatorcontrib><creatorcontrib>Ma, Junyun</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Managerial and decision economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Feng, Qun</au><au>Hua, Wei</au><au>Chen, Chuanhao</au><au>Shi, Xuejun</au><au>Ma, Junyun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization of cold chain logistics distribution paths for community buying considering cost and time window: The case of J Center</atitle><jtitle>Managerial and decision economics</jtitle><date>2024-12</date><risdate>2024</risdate><volume>45</volume><issue>8</issue><spage>5249</spage><epage>5264</epage><pages>5249-5264</pages><issn>0143-6570</issn><eissn>1099-1468</eissn><abstract>In recent years, the community group buying market has been developing rapidly, and the group buying categories are mainly fresh food, so one of the keys to the success of the community group buying platform lies in the supply chain logistics, in which the cold chain logistics is the key to guarantee the fresh food products for the time and quality. In this paper, on the combing research of the theories and problems of community group purchase, cold chain logistics, and vehicle path planning, in view of the existing problems of cold chain logistics and distribution business in Jinan distribution center of J company's community group purchase, taking into account the actual demand of the grid station and the characteristics of the fresh products to be stored at low temperatures, we constructed the optimization model of the cold chain logistics and distribution path that minimizes the total cost under the demand of the fuzzy time window of the grid station, and designed the distribution area is divided by using K‐means clustering, and then, the distribution path in each sub‐distribution area is optimized and solved by genetic algorithm, and then, the validity of the optimization scheme is verified, the number of distribution trucks used is reduced by two, and the distribution cost is reduced by 12.77%, and optimization measures such as promoting the standardization of warehousing and distribution, and creating a digital and integrated logistics information platform are proposed.</abstract><cop>Chichester</cop><pub>Wiley Periodicals Inc</pub><doi>10.1002/mde.4319</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0003-1442-9695</orcidid></addata></record> |
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subjects | Clustering Cold storage Community Community organizations Distribution costs Fuzzy logic Genetic algorithms Logistics Optimization Standardization Supply Supply chains Warehousing |
title | Optimization of cold chain logistics distribution paths for community buying considering cost and time window: The case of J Center |
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