How Better Optimization Can Solve Supply Chain Issues

Author: Gregory Glockner, PhD

For many businesses, “optimizing” their operations means finding the least expensive (or most profitable) solution. This might mean choosing the cheapest resources or moving production to countries with a lower cost of labor. This strategy can save companies money and increase profit margins in the short term, but what if some disruptive event—like a war or global pandemic—makes those resources unavailable?

Such disruptions can bring your business to a standstill. That’s why optimizing for costs alone isn’t enough; you need to consider other factors, particularly robustness.

Rather than focusing exclusively on cutting costs, it’s important to think about the regions, labor, and skills your business depends on. But as the world’s current supply chain issues show us, many businesses have not had this foresight. In this article, we’ll take a look at how optimizing for robustness can protect our supply chains moving forward.

What supply chain shortages teach us about optimization

Following World War II, the U.S. found itself in the middle of a manufacturing boom. But as the country shifted toward the service industry, other countries, especially those in Asia, were ready to pick up the slack.

Because labor and materials are so relatively cheap in countries like China, the U.S. and others began to shut down their own manufacturing plants and rely solely on those countries for cheaper production.

As we’ve all witnessed over the last two years, the shutdown of Chinese factories due to COVID-19 in 2020 led to serious supply chain issues and shortages. The world was caught off guard, since so many countries relied on that one region for manufacturing.

Today, the war in Ukraine is also rocking global supply chains in a palpable way, and it’s not just about oil.

For example, most of the world’s neon comes from Ukraine. Semiconductor manufacturers rely on neon to control the lasers used to make computer chips. This means that the turmoil in Ukraine could worsen the current chip shortage even further, impacting the production of everything that has a chip, from electronics to cars and planes.

Russia and Ukraine are also in a region known as the “world’s breadbasket.” The two countries account for over 30% of global wheat exports, and since the conflict started, wheat prices have surged by over 40%. In Italy, a country that imports most of its wheat from Eastern Europe, prices of bread and pasta have already risen significantly.

Optimizing for robustness vs. cost alone

So what does all of this have to do with optimization? These cases of supply chain shortages demonstrate the dangers of “putting all our eggs in one basket.”

Sure, labor and factories may be cheaper in China, but we’ve seen now what happens when we depend on one region for manufacturing (or anything, for that matter).

Returning to the example of neon, it’s not that we can only find it in Ukraine—but that’s where most production plants are. The process of capturing and distilling neon into liquid form is very complex, which is why it’s more convenient to use a facility that’s already applying the same technology for other reasons.

However, we could put these plants anywhere in the world—for example, in the northwestern U.S., where there is cheap hydroelectric power, or in China or Taiwan, near semiconductor manufacturers.

In the case of computer chips, we might keep three-quarters of our production capacity in China, but the remaining quarter somewhere else, like the U.S. Although it’s not the cheapest option, it protects against regional instability.

Whether your business is dependent on neon, wheat, or any other material, having multiple sources can decrease your vulnerability to unexpected disruptions because you’ll have other options to fall back on.

This is how the world must learn to adapt, and optimization needs to play a role. However, we need to optimize wisely and look not just at costs, but also at stability, resiliency, and robustness.

How Gurobi can help

Optimizing for cost is relatively simple, since all you need to do is choose the least expensive option. But if you want to optimize for robustness, you must consider multiple factors—such as speed, quality, and location—in addition to costs. Finding and choosing a plan that balances these targets can become extremely complex, but an optimizer like Gurobi can help.

With Gurobi, simply input the goals you want to achieve and the solver will sort through the trillions of options that could satisfy those goals. Gurobi will then identify the best solution for you, often within seconds. If at any point you wish to make a change, simply modify your inputs and run the solver again. This makes it possible to consistently reach optimal business outcomes while protecting against massive disruptions in an ever-changing business environment.