Strengthening Resilience for Critical Supply Chain Networks: Strategic Optimization and Decision Support

As global supply chains become more interconnected and complex, strengthening their ability to anticipate, manage, and recover from disruptions presents a growing challenge, particularly in critical sectors such as food and pharmaceuticals, where disruptions can have severe consequences. Resilience in these contexts involves strategic planning approaches that strengthen supply networks, improve transparency across operations, and support targeted responses to disruptions. These capabilities enable both public authorities and companies to manage operations more effectively, monitor performance, and maintain the continuity of supply. While interest in supply chain resilience is rising, there is still considerable potential for deeper evaluations of network strategies, datadriven decisions, and insights from real-world case studies. Given these challenges, this dissertation presents six research studies that propose strategic optimization and decision support methodologies, contributing to resilience in critical supply chain networks.
Study A focuses on optimizing facility placement and the distribution of critical goods, accounting for disruptions in warehouse availability and operability, route failures, coverage limitations, and demand variability. ... mehrStudy B addresses network design under varying impact scenarios, integrating location-allocation decisions to minimize shortages and leverage economies of scale in storage. The study employs stochastic modeling to assess crisis intensity, facility size, capacity limits, and cost-weighting strategies.
The models in Studies A and B are applied to Germany’s national food stockpiling system, demonstrating their applicability and practical relevance. Study C analyzes national food stockpiling strategies through a comparative analysis of different countries, highlighting their benefits and limitations. Study D introduces a routing model that optimizes fleet composition by balancing the strengths of different vehicle types, such as trucks and drones, and considers the specific requirements of humanitarian logistics. A case study based on the COVID-19 pandemic assesses the model’s relevance and sensitivity. Study E develops a Knowledge Graph to systematically structure, link, and integrate heterogeneous data sources, enabling a comprehensive analysis of drug shortages and supporting complex queries to uncover contributing factors and enhance strategic planning. Study F deepens the understanding of supply chain resilience in the pharmaceutical sector. It emphasizes the strategic importance of resilience-building capabilities and proposes a structured approach to link them with sector-specific vulnerabilities.
Beyond the findings of the studies, this dissertation offers overarching implications across key areas, including network design, disruption management, data-driven decisions, and the development of strategic insights for diverse stakeholders. Collectively, these outcomes provide valuable contributions to strengthening the resilience of critical supply chain networks.