Towards Resilience: “Quickly” Re-optimizing Large-scale Problems
Our rapidly changing world is characterized by unpredictable events and growing uncertainty levels. Technological advancements, global economic shifts, geopolitical tensions, and environmental challenges are some factors contributing to this trend. This change presents new opportunities for growth and innovation. By embracing it, being agile and adaptable, and working together, we can navigate these uncertainties and create a better future for ourselves and future generations.
“Resilience is the ability to recover from or adjust easily to misfortune or change” — Merriam-Webster Dictionary
In this article, we explore large-scale re-optimization as a potential way to achieve resilience in large-scale contexts. We consider the case of supply chains for illustration.
Large-scale Optimization
Large-scale optimization is a field of mathematics that deals with finding the best possible solution to complex problems involving millions of variables and constraints. It is used in various industries, including finance, transportation, energy, logistics, and engineering. The goal is optimizing processes and systems, improve efficiency, minimize costs, and maximize performance. The importance of large-scale optimization lies in its ability to find solutions for complex problems that are difficult or impossible to solve using traditional methods (e.g., manual methods). Organizations can make better decisions and improve efficiency using large-scale optimization. It can also help identify new opportunities for growth and innovation.
Resilience
Among several definitions, resilience can be defined as an organization’s ability to recover quickly from unexpected events (perturbations and disruptions), such as natural disasters, economic downturns, cyber-attacks, or pandemics. In today’s volatile and rapidly changing business environment, companies must be resilient to survive and thrive. Resilient companies are better equipped to adapt to changing circumstances, identify and manage risks, and recover quickly from setbacks.
Qualitative Perspective of Resilience
From a qualitative perspective, supply chain resilience is only about restoring normal operations after a disruption but also about learning and adapting to prevent future perturbations. It involves developing a culture of resilience that values proactive risk management, continuous improvement, and collaboration. It also highlights the importance of relationships and collaboration. Strong relationships and partnerships with suppliers, customers, and other stakeholders can provide a network of support and resources that helps the supply chain quickly recover from perturbations.
Quantitative Perspective of Resilience
The quantitative perspective of supply chain resilience focuses on developing mathematical models and algorithms to quantify supply chain resilience and identify the best strategies to enhance it. It involves measuring the impact of perturbations on the supply chain, assessing the effectiveness of different strategies in reducing the perturbations’ effect, and optimizing the allocation of resources to improve resilience. In this perspective, we measure supply chain resilience through key performance indicators such as recovery time, inventory levels, and customer service targets.
Re-optimization
Large-scale re-optimization supports supply chain resilience improvement by identifying and addressing vulnerabilities and inefficiencies that can lead to perturbations. To do so, one must analyze the supply chain’s design, network structure, inventory levels, and transportation routes to identify potential risks and develop mitigation strategies. Large-scale re-optimization is crucial for supply chain resilience because it allows organizations to make data-driven decisions about resource allocation and the supply chain’s performance improvement. By using mathematical models and algorithms to analyze the supply chain and identify opportunities for improvement, organizations can build a more resilient and efficient supply chain that can withstand and recover from perturbations.
Re-optimization after Perturbation
Mathematical re-optimization after perturbation can be used to respond to minor changes such as transportation delays, weather in a port, or supplier bankruptcies. A perturbation is generally a small and short-lived disturbance that may not require significant intervention to address. For example, suppose a supplier in the supply chain experiences a perturbation that leads to a delay in the delivery of raw materials. In that case, the organization can use mathematical models and optimization algorithms to re-optimize the supply chain and adjust the production schedule to minimize the impact of the delay.
Re-optimization after Disruption
Re-optimization for the supply chain after a disruption is more complex. A disruption is a severe and potentially long-lasting disturbance that requires significant attention and intervention, such as disasters, tsunamis, or earthquakes. In such a context, re-optimization involves using mathematical models and optimization algorithms to adjust and optimize the supply chain in response to the disruption caused by the disaster. It can be a complex and challenging task, as disasters can have a significant impact on the supply chain’s network, transportation infrastructure, and production facilities.
Quick large-scale re-optimization is a crucial way to achieve supply chain resilience. The ability to quickly and effectively respond to perturbations and disruptions and adapt to changing conditions is essential for ensuring the continuity of supply chain operations and minimizing the perturbations and disruptions’ impact on customers, suppliers, and stakeholders.
What do you think about the presented insights? I am looking forward to hearing your ideas :-)
