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

Area of Science:

• Operations Research
• Supply Chain Management
• Optimization

Background:

• Globalization and cost-cutting measures have heightened supply chain vulnerability.
• Effective risk mitigation strategies are crucial for modern production settings.
• Supply chain disruptions pose significant financial risks to manufacturers.

Purpose of the Study:

• To develop an effective risk mitigation strategy for supply chain disruptions in a production setting.
• To minimize total production cost for a manufacturer by optimizing disruption mitigation strategies.
• To reduce manufacturer regrets in disrupted scenarios using a novel bilevel optimization framework.

Main Methods:

• A bilevel optimization framework is employed to model the problem.
• The framework formulates a convex network flow program with a chance constraint on manufacturer regrets.
• Generalized Benders decomposition and customized feasibility cuts are used for efficient problem-solving.

Main Results:

• The research analyzes supply chain disruptions and manufacturer regrets.
• Regrets are defined as the cost difference between reactive and anticipative production plans.
• The proposed mitigation strategy reduces regrets for long disruptions at the expense of shorter ones.

Conclusions:

• The study offers a method to decrease production costs, particularly under rare but high-impact disruption scenarios.
• Managerial insights into risk-adjusted production are provided.
• The framework effectively balances the impact of different disruption lengths on overall costs.