A System Dynamics Model and Interface for the Simulation and Analysis of Milk Supply Chains

Author(s):  
Georgios Tsaples ◽  
Theodore Tarnanidis

The objective of this chapter is the development of a System Dynamics model for the study of the milk supply chain and how an extreme event can affect its behavior. A simple interface is developed that can be used to increase the ease of communication and provide an interactive approach to the decision-making process. The model contains three echelons: farmers, processors and retailers. The main results show that under normal circumstances, the behavior of the system reaches equilibrium after a few oscillations. However, these oscillations can be smoothed out if the adjustment time of the order placement is increased. Under an extreme event that reduces the demand for milk, behavior changes and the system remains in dis-equilibrium for the entire simulation. Once again, adjustment times remain the leverages that can influence and mitigate those negative effects. Finally, a more robust and collaborative decision-making process among the actors of the chain could be beneficial for all not only under normal circumstances, but also in the presence of extreme uncertainty.

Author(s):  
Georgios Tsaples ◽  
Theodore Tarnanidis

The objective of this chapter is the development of a System Dynamics model for the study of the milk supply chain and how an extreme event can affect its behavior. A simple interface is developed that can be used to increase the ease of communication and provide an interactive approach to the decision-making process. The model contains three echelons: farmers, processors and retailers. The main results show that under normal circumstances, the behavior of the system reaches equilibrium after a few oscillations. However, these oscillations can be smoothed out if the adjustment time of the order placement is increased. Under an extreme event that reduces the demand for milk, behavior changes and the system remains in dis-equilibrium for the entire simulation. Once again, adjustment times remain the leverages that can influence and mitigate those negative effects. Finally, a more robust and collaborative decision-making process among the actors of the chain could be beneficial for all not only under normal circumstances, but also in the presence of extreme uncertainty.


2012 ◽  
Vol 461 ◽  
pp. 474-477
Author(s):  
Quan Li Huang ◽  
Jing Tao Yue ◽  
Yu Lan Ding

According to the establishment of the simulation model about urban integrated transportation system, this paper established kinematics model of the urban integrated transportation system by the core application of system dynamics theory, technical methods and special tools. This model provided a scientific basis and technical methods to intelligent control and Optimizing the decision-making for urban integrated transportation.


2016 ◽  
Vol 15 (S1) ◽  
Author(s):  
Alexandra Macmillan ◽  
Michael Davies ◽  
Clive Shrubsole ◽  
Naomi Luxford ◽  
Neil May ◽  
...  

2019 ◽  
Vol 11 (10) ◽  
pp. 2806 ◽  
Author(s):  
Yuliya Mamatok ◽  
Yingyi Huang ◽  
Chun Jin ◽  
Xingqun Cheng

With the rapid development of the container shipping industry, the mitigation of carbon dioxide (CO2) emissions from container seaport activities have become an urgent problem. Therefore, the purpose of this research is to investigate dynamic problems in mitigation strategies at a container seaport. As a result, a system dynamics model for CO2 mitigation strategies at a container seaport was established. Three methods were combined to construct the system dynamics model: the activity-based method to estimate CO2 emissions; the representation of a container seaport as a system with several sub-systems; the system dynamics modeling for strategic decision-making in CO2 mitigation strategies. The key model component was the amount of CO2 emissions produced by container seaport activities. The other components represented container seaport operations and the main spots of CO2 concentration at berth, yard, gates, and region areas. Several CO2 mitigation strategies were included in the model to be simulated. The real case of Qingdao Port in China was used to simulate the scenarios of the current situation with CO2 emission amounts and the increasing container throughput. The other scenarios demonstrate the effects from CO2 mitigation strategies, such as operating time optimization, spatial measures, equipment modernization, and modal shift. The obtained results enable container seaport executives to evaluate which mitigation scenario is more effective for every container seaport area. The system dynamics model serves as a useful decision-making mechanism providing flexibility and variability in strategic planning.


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