Entropy-Based Algorithm for Supply-Chain Complexity Assessment
AbstractThis paper considers a graph model of hierarchical supply chains. The goal is to measure the complexity of links between different components of the chain, for instance, between the principal equipment manufacturer (a root node) and its suppliers (preceding supply nodes). The information entropy is used to serve as a measure of knowledge about the complexity of shortages and pitfalls in relationship between the supply chain components under uncertainty. The concept of conditional (relative) entropy is introduced which is a generalization of the conventional (non-relative) entropy. An entropy-based algorithm providing efficient assessment of the supply chain complexity as a function of the SC size is developed. View Full-Text
A printed edition of this Special Issue is available here.
Share & Cite This Article
Kriheli, B.; Levner, E. Entropy-Based Algorithm for Supply-Chain Complexity Assessment. Algorithms 2018, 11, 35.
Kriheli B, Levner E. Entropy-Based Algorithm for Supply-Chain Complexity Assessment. Algorithms. 2018; 11(4):35.Chicago/Turabian Style
Kriheli, Boris; Levner, Eugene. 2018. "Entropy-Based Algorithm for Supply-Chain Complexity Assessment." Algorithms 11, no. 4: 35.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.