Quantifying, Reducing, and Repurposing Wasted Food

The MathWorks Math Modeling (M3) Challenge—a competition that encourages participants to use critical thinking and computational methods to quantify open-ended, real-world problems—poses prominent, multi-faceted issues to U.S. high school juniors and seniors, who compete on teams of three to five. To make the contest accessible to all participants regardless of their prior exposure to mathematical modeling, SIAM is constantly on the lookout for interesting problems that enable teams to find data and implement approaches with varying degrees of simplicity or complexity. Exposing thousands of future leaders and innovators to important topics in applied mathematics is among SIAM’s priorities.

Judges for the contest—who numbered about 130 this year—anticipate the commendable creativity and insights displayed by students in their solution papers, motivated by a passion for mathematical applications and a shot at winning part of the $100,000 in scholarship awards funded by MathWorks. 912 teams—comprised of 4,175 high school juniors and seniors—submitted solution papers in the 2018 Challenge, each vying for one of 40 monetary prizes.

The 2018 Challenge problem focused on food insecurity. It posited that “ugly,” uneaten, leftover, and excess food waste from households, cafeterias, restaurants, and grocery stores is not “trash,” but rather wasted food. Could a community feed those experiencing food insecurity by thoughtfully repurposing food squandered by others? How do we quantify the amount of food wasted annually? How can we redirect wasted food to benefit those in need? The problem posed a few specific household scenarios—single parent, family of four, etc.—on which to demonstrate models (though students could certainly utilize their own household structures), and asked for model-based strategies to repurpose the most food for the least cost.

Karen Bliss (Virginia Military Institute), Katie Kavanagh (Clarkson University) and Ben Galluzzo (Shippensburg University), who comprise the Challenge’s problem development committee, crafted the 2018 problem, entitled “Better ATE than Never: Reducing Wasted Food” (see sidebar). Since 2012, the committee has formulated or refined submitted problem ideas, enabling the contest to demonstrate the use and value of mathematics in computation-based decisions while bringing visibility and novel thought to relevant, timely, and newsworthy topics. To ensure that the questions are authentic and realistic, the group often recruits and collaborates with professionals with expertise in the underlying area. The U.S. Department of Agriculture’s Economic Research Service weighed in on this year’s problem. 

We asked problem development committee members: what motivated this year’s problem on food waste?

Karen Bliss

We felt very strongly that this year’s question should have a local tie-in, so participants felt connected to the topic. In addition to understanding the mathematics of it all, we wanted students to think about how they could apply modeling to a community to which they belong right now, be it their school, town, or state. We are hoping that students see how they can utilize applied mathematics in very concrete ways to assist those in need around them.

I was surprised by the volume of data available regarding food production, food consumption, and the severity of food insecurity. It became clear that researchers are actively studying this very worthy topic, and it will certainly be exciting to see how teams tackle the complex questions we posed. We wanted to introduce available data with the problem, since last year’s Challenge question—which included data for students to grapple with as they did their modeling—was well received. 

While modeling is certainly distinctly different from statistics and/or simply data-fitting with appropriate lines and curves, we hope that the provided data gave students a sense of what factors they might consider when building their models. 

I cannot wait to hear how many teams show their work to their schools, towns, etc., to raise awareness for this cause and inspire action. That will be incredibly powerful.

Katie Kavanagh

My mathematical area of research is optimization, so my mind is programmed to look for ways to increase efficiency. I also have a decent-sized garden, so I care deeply about the time, labor, and resources that go into planting a seed and fostering it to grow into nourishment. Furthermore, I live in a rural, poverty-stricken region of upstate New York, where over 80 percent of the children in most of our school district are eligible for reduced or free lunch; it is the only daily meal some of them get. All of these factors motivated me to focus a problem on this critical subject.

Mathematically, modeling human behavior is complex and interdisciplinary, with a wide range of challenges. What factors and human characteristics lead one person to toss something out and another to make soup from their leftovers? What is the food industry’s tipping point to produce the quantity that is actually needed and distribute it accordingly, so that the least possible amount winds up in a landfill? Luckily, certain initiatives provide data that could be useful in answering these questions. Mathematics can play a significant role in quantifying the amount of unconsumed food versus the amount that is actually grown, and designing and analyzing strategies to repurpose these resources. These are the driving ideas behind these questions; how much is wasted, how many are hungry, and can we close the gap? How do we model human behavior when it comes to food choices? How can we make changes?

Although it seems like this is a problem for agricultural economists and social scientists, I genuinely believe that talented and motivated high school students will come up with some innovative approaches. They see the behavior of their peers in the cafeteria and observe how their family prepares meals and shops for groceries. They may even stop and think about these actions the next time they decide to toss their brussels sprouts in the garbage. Students have access to a wide range of data and computational tools with which to create meaningful mathematical models, but their personal experiences and communities will also play a key role in their results. It may not even be upper-level mathematics content that leads to the most sophisticated model, though a successful solution will require innovation and a willingness to dive into the problem. 

I am so excited to see what they come up with, and hope that they feel as passionately about the topic as I do.

Ben Galluzzo

The dining hall at Shippensburg University went “tray-less” a number of years ago, and noted a significant decrease in uneaten food as a result. Likely due to my knowledge of this data, as well as historical reminders that one should finish a meal with a “clean” plate, I assumed that “leftover” or uneaten prepared food accounted for most food waste. 

However, two events brought the magnitude of food waste into perspective, so much so that they convinced me this was a problem worth investigating. First, Katie shared a National Geographic article that highlights the overwhelming amount and types of perfectly fresh, unprepared food that is squandered via the supply chain. The reported numbers—2.9 trillion pounds of food, or about a third of global food production—are staggering. Soon after reading this article, I spent a day volunteering at the Central Pennsylvania Food Bank, sorting produce for redistribution to agencies across the region that provide assistance to food-insecure individuals. It was simultaneously surprising and disturbing to see and touch hundreds of pounds of completely fresh, remarkably “normal” produce—such as green peppers, potatoes, and eggplants—that had been identified as unsellable to the general public and, without intervention, would have been thrown away. Following this revelation, a conversation with Food Bank employees about their efforts to redistribute food, including produce and nonperishable items found in their warehouse, reinforced to me the nontrivial, resource-heavy work that they perform on a daily basis. I left this experience motivated to find more data on the topic of food waste and truly interested in exploring ways to redistribute food. 

Who better to tackle this issue than motivated, talented high school students who will likely face firsthand some of the consequences of food insecurity in the decades to come? I look forward to reading about how participants choose to use mathematical modeling to approach this important topic.