文献类型：期刊文献

英文题名：Deterioration rate variation risk for sustainable cross-docking service operations

作者：Pan, Fei[1]; Zhou, Wei[2,3]; Fan, Tijun[1]; Li, Shuxia[1]; Zhang, Chong[1]

机构：[1] School of Business, East China University of Science and Technology, Shanghai, 200237, China; [2] Information & Operations Management, ESCP Europe, Paris, 75011, France; [3] Transportation Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiaotong University, Shanghai, 200240, China

年份：2021

卷号：232

外文期刊名：International Journal of Production Economics

收录：EI(收录号：20204309400944)

语种：英文

外文关键词：Risk assessment - Docking - Scheduling - Trucks - Integer programming - Risk analysis - Genetic algorithms

摘要：Modern service platforms are characterized by heterogenous products collected and re-distributed from different suppliers to many buyers. Based on the recent findings from the food science/engineering literature, we identify a new phenomenon of deterioration rate variation risk in the context of sustainable cross-docking service. A perishable product's deterioration rate may vary due to the unstable logistic environment that is typically found on the cross-docking service platform. Products’ deterioration and on-site environmental information is collected by the IoT and sensor system. A mixed-integer programming model is formulated to model the perishable product truck scheduling problem on the cross-docking platform. Based on a customized genetic algorithm, the numerical analyses are conducted on 4 scenarios and 20 instances. Results show significant benefits of incorporating the deterioration rate variation risk analysis on a multi-supplier multi-buyer multi-product cross docking service platform. ? 2020 Elsevier B.V.