Reorganization of Logistics Network

Cross-dock is defined as the practice of unloading goods from incoming vehicles and loading them directly into outbound vehicles. Cross-docking can simplify supply chains and help them to deliver goods to the market more swiftly and efficiently by removing or minimizing warehousing costs, space requirements, and use of inventory. Regarding the lifetime of perishable goods, their routing and scheduling in the cross-dock and transportation are of great importance. This study aims to analyze the scheduling and routing of cross-dock and transportation by System Dynamics (SD) modeling to design a reverse logistics network for the perishable goods. For this purpose, the relations between the selected variables are first specified, followed by assessing and examining the proposed model. Finally, four scenarios are developed to determine the optimal values of decision variables. The results indicate the most influencing factors on reaching the optimal status is the minimum distance between the cross-dock and destination, rather than increasing the number of manufactories.

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Logistics network design to reuse second-hand household appliances for charities

Journal of Cleaner Production ◽

10.1016/j.jclepro.2019.118717 ◽

2020 ◽

Vol 244 ◽

pp. 118717 ◽

Cited By ~ 3

Author(s):

Abdolhossein Sadrnia ◽

Najme Roghani Langarudi ◽

Amirreza payandeh Sani

Keyword(s):

Network Design ◽

Household Appliances ◽

Logistics Network

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Quality tracing in meat supply chains

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2013.0308 ◽

2014 ◽

Vol 372 (2017) ◽

pp. 20130308 ◽

Cited By ~ 16

Author(s):

Miriam Mack ◽

Patrick Dittmer ◽

Marius Veigt ◽

Mehmet Kus ◽

Ulfert Nehmiz ◽

...

Keyword(s):

Supply Chains ◽

Process Analysis ◽

Decision Support Tool ◽

Temperature Monitoring ◽

Support Tool ◽

Logistics Network ◽

Primary Model ◽

Sensory Parameters ◽

And Storage

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

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