Modeling and mitigating supply chain disruptions as a bilevel network flow problem

Abstract Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze disruptions in a production setting. Using bilevel optimization framework, minimize the total manufacturer interested finding optimal disruption The problem constitutes convex network flow program under chance constraint bounding manufacturer’s regrets disrupted scenarios. Thus, contrast to standard schemes with two decision-makers, leader follower, model searches plan view reduction sequence his own scenario-specific regrets. Defined as difference costs reactive , which considers unknown until it occurs, benchmark anticipative predicts beginning planning horizon, allow measurement impact strategies on cost. For an efficient solution problem, employ generalized Benders decomposition develop customized feasibility cuts. managerial section, discuss implications risk-adjusted observe that long are reduced strategy at shorter disruptions, whose typically stay far below threshold. This allows decrease rare but high-impact