Maximum Relative Divergence Principle for Grading Functions on Direct Products of Chains
arXiv:2303.14261
Abstract
The concept of Shannon Entropy for probability distributions and associated Maximum Entropy Principle are extended here to the concepts of Relative Divergence of one Grading Function from another and Maximum Relative Divergence Principle for grading functions on direct products of totally ordered chains (chain bundles). Several Operations Research applications are analyzed.