Abstract
A drastic change occurs in the logistics business from over the past 20 years. In today’s scenario, a novel logistic approach is a requirement. Due to the difficulties in integrating the information and dynamic changes in the situation, the logistic approach planning becomes more challenging. The logistics planning process can be useful if the data can be integrated from various partners to generate the combined knowledge. This paper presents a machine learning based adaptive framework for logistics planning and digital supply chain the new industrial revolution is useful to Logistics Processes like Cyber-Physical System. It is explained which are the technical components of digital logistics and supply chain. The proposed system will grow, acclimate and expand as its knowledge grows to provide a generalized solution to all kinds of logistics and supply chain activities.
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Chaudhary, K., Singh, M., Tarar, S., Chauhan, D.K., Srivastava, V.M. (2018). Machine Learning Based Adaptive Framework for Logistic Planning in Industry 4.0. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 905. Springer, Singapore. https://doi.org/10.1007/978-981-13-1810-8_43
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