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Entropy-Based Algorithm for Supply-Chain Complexity Assessment

School of Economics, Ashkelon Academic College, Ashkelon 84101, Israel
Department of Computer Science, Holon Institute of Technology, Holon 58102, Israel
Author to whom correspondence should be addressed.
Algorithms 2018, 11(4), 35;
Received: 28 February 2018 / Revised: 20 March 2018 / Accepted: 21 March 2018 / Published: 24 March 2018
(This article belongs to the Special Issue Algorithms for Scheduling Problems)
PDF [320 KB, uploaded 3 May 2018]


This 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
Keywords: industrial supply chain; supply chain complexity; information entropy industrial supply chain; supply chain complexity; information entropy

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Kriheli, B.; Levner, E. Entropy-Based Algorithm for Supply-Chain Complexity Assessment. Algorithms 2018, 11, 35.

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