Abstract
Due to mismanagement of supply chain operations, fresh produce, which deteriorates highly depending on time and operating environment (including temperature and humidity), will suffer huge losses in transit, resulting in substantial monetary losses. Cross-docking, as an efficient logistics operation strategy, has been widely used in fresh produce distribution in the cold supply chain, whereas it has not received adequate attention in the scientific literature. In order to improve the efficiency of fresh produce distribution, this study formulates a novel mixed-integer mathematical formulation model that allows repeated loading of outbound trucks to minimize the total deterioration (TD) of all the fresh produce in the cross-docking center. To solve this problem, an advanced genetic algorithm is proposed based on a constructional mixed chromosome with two parts and three levels. The numerical analyses are conducted on 10 typical instances under different combinations of parameters. Results show that our proposed model based on the repeated loading mode can effectively decrease the total deterioration compared with the traditional nonrepeated loading mode. And this superiority becomes more significant, as the value of truck changeover time and lot loading quantity (called lot size in the text) decrease. In particular, when the truck changeover time equals 0, the total deterioration obtained under repeated loading mode will be more than 31.8% on average smaller than that under nonrepeated loading mode.
Highlights
Fresh produce, including fruits, vegetables, meat, and seafood, damage greatly during supply chain operations, which leads to great losses of revenues in fresh produce supply chains [1,2,3]
Erefore, the deterioration process of a batch quantity xijk fresh produce within the cross-docking center can be divided into three stages: (1) the first stage is from time 0 to the time when the products start to be unloaded from inbound truck i (i.e., Ci); (2) the second stage is from Ci to the time when the products are loaded onto outbound truck j
We formulate a truck scheduling model for the crossdocking of fresh produce under repeated loading mode and present a definition of the total deterioration (TD) that considers the operation times, deterioration rates, and quantities corresponding to different types of fresh produce
Summary
Fresh produce, including fruits, vegetables, meat, and seafood, damage greatly during supply chain operations, which leads to great losses of revenues in fresh produce supply chains [1,2,3]. Is paper formulates a novel mixed-integer mathematical formulation model and proposes a solution framework based on the genetic algorithm (GA) with repeated loading of outbound trucks to minimize the total deterioration (TD) of all the fresh produce in the crossdocking center. A classic cross-docking model with infinite temporary storage capacity was constructed by Yu and Egbelu [22]; they proposed nine heuristic algorithms for determining the optimal truck schedules for inbound and outbound trucks to minimize the total operation time. Alpan et al [39] presented a cross-docking environment with multiple receiving and shipping doors, where the objective function was formulated to determine the optimal flexible schedule for inbound and outbound trucks that could minimize the total operational cost. Erefore, we propose a cross-docking scheduling model for fresh produce with repeated loading. e objective is to determine the optimal schedule for inbound and outbound trucks that minimizes the Total Deterioration (TD) of all fresh produce
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
