Managing Supply Chains A Logistics Approach 9th Edition Pdf Chapter 2
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Many government departments or non-profit organizations were also built to help with food safety, such as FDA in America, Food Standards Agency in the UK, State Food and Drug Administration in China, etc. The global supply chains are more complex with different policies to adapt in different areas, and give global companies more pressure for traceability. By applying blockchain, globalized standardization can be adaptable for all countries and regions, and they can save companies from duplicative works . For sustainability purposes, traceability is also a way to monitor environmental impacts, therefore, encouraging companies to be more sustainable.
Descriptive analysis is the first insight into all of the papers, to provide basic information of the selected papers. Among the selected papers, the earliest paper (one out of 26) was released in 2016, and nine papers in 2017, and 16 papers were from 2018, due to the young age of technology. The time trend shows that blockchain is gaining increasing attention and interest in the supply chain area. This also explains why 13 out of 26 papers are technology and innovation related conference papers. Although all of the papers are focused on the food supply chain, the food categories are slightly different. Most of the papers focused on agri-food supply chain in general [17,22,28,55,56,57,58,59,60,61]. A few papers used more specific food supply chains, such as Halal supply chain , tilapia supply chain , and rice supply chain . Papers mainly introduced blockchain and demonstrate its potential by using conceptual framework (13 out of 26), and then pilot cases (seven out of 26), three theory papers (three out of 26), one survey (one out of 26), and two systematic literature analyses (two out of 26), respectively.
Reinforcement: Reinforcement learning is a type of machine learning algorithm that enables software agents and machines to automatically evaluate the optimal behavior in a particular context or environment to improve its efficiency , i.e., an environment-driven approach. This type of learning is based on reward or penalty, and its ultimate goal is to use insights obtained from environmental activists to take action to increase the reward or minimize the risk . It is a powerful tool for training AI models that can help increase automation or optimize the operational efficiency of sophisticated systems such as robotics, autonomous driving tasks, manufacturing and supply chain logistics, however, not preferable to use it for solving the basic or straightforward problems.
Reinforcement learning, along with supervised and unsupervised learning, is one of the basic machine learning paradigms. RL can be used to solve numerous real-world problems in various fields, such as game theory, control theory, operations analysis, information theory, simulation-based optimization, manufacturing, supply chain logistics, multi-agent systems, swarm intelligence, aircraft control, robot motion control, and many more. 2b1af7f3a8