Selection of Anti-Risk Programs for Reducing Losses on Supply Chains

A problem to select strategic programs destined for reducing losses induced by failures or other undesirable events in the supply chain is considered. It is offered to solve the problem in two stages. At the first stage, the identification of most informative components (subsystems) of the chain is performed from the standpoint of amount of the information on risks and appropriate losses, which makes it possible to minimize the data volume, to reduce a size of the chain graph and, as a result, to simplify the selection procedure at the second stage. Using Shannon’s information entropy is proposed for measuring the self-descriptiveness of subsystems of complex supply chains. At the second stage, a mathematical problem for selecting the antirisk program portfolio (presented as a problem of mathematical programming of knapsack type) is solved on the simplified graph of supply chain. A new algorithm of solving the problem for anti-risk program selection is proposed.

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