Due to increasing diversity and growing size of modern industrial supply chains, today problems of identification, assessment and mitigation of disruption risks become challenging goals of the supply chain risk management. In this paper, we focus on environmental (ecological) risks in supply chains which represent threats of adverse effects on living organisms, facilities and environment by effluents, emissions, wastes, resource depletion, etc. arising due to supply chain’s activities. Harmful environmental disruptions may ripple through the supply chain components like a wave. The paper presents the entropy-based optimisation model for reducing the supply chain model size and assessing the economic loss caused by the environmental risks subject to the ripple effect. A main advantage of the suggested entropy-based approach is that it permits to essentially simplify the hierarchical tree-like model of the supply chain, at the same time retaining the basic knowledge about main risk sources.

We consider a problem of quantifying risk factors and identifying most informative (or vulnerable) components of the supply chain in terms of the amount of information about the risks and corresponding losses. This knowledge is beneficial for the selection of risk-prevention decisions. Shannon’s entropy is shown to be a powerful tool for risk management in hierarchical supply chains. An efficient algorithm is proposed that permits to reduce the size of the supply chain model without a loss of essential information about the risks and their economic consequences. A case study is presented to demonstrate the validity of the entropy-based approach.

Птускин А.С. Построение периодического расписания транспортных роботов гибких автоматических линий // Стратегическое планирование и развитие предприятий: