# M3 Challenge 2018 - WPI - Worcester Polytechnic Institute

## M3 Challenge 2018 - WPI - Worcester Polytechnic Institute

Team 10933 1 M3 Challenge 2018 Executive Summary Every night in America, thirteen million children go to bed with a gaping hole in their bellies where a healthy meal should be. Forty-one million people in total end the day wondering where and when their next meal will be coming. Despite the struggle of so many people in our country to provide enough food for themselves and their families, almost 31% of available food is thrown away due to its appearance or store-given “best by” date. This causes an estimated loss of \$161.6 billion in the United States economy, and begs the question: can the large amounts of wasted food be used to solve the hunger crisis in America?

In the first aspect of the problem, we were tasked with designing a model capable of determining if the state wasted enough food per year to feed the parts of the population that are food-insecure. Our model calculated the total amount of money it would require to supply the food-insecure population with 3 full meals per day for an entire year, while accounting for the average cost per meal, number of food-insecure people, and total state population. The second part of the model calculated the value of food wasted by consumers and outlets per year, accounting for the total amount of money in food wasted per year nationwide, the amount of food that is wasted that can not be redistributed, and the state population.

Based on the model, if the total value of food wasted was larger than the cost to feed all food-insecure people, the state should be able to feed its food insecure population with its wasted food. This model was tested with data from the state of Texas, which, based on our model, was proven to have enough wasted food to feed the food-insecure people.

The second portion of the challenge instructed us to create a model that would determine the amount of waste a household generated, based on the personal choices, traits, and habits of individual households. Our model takes into account the age of the occupants of the household, the household’s total yearly income, and the number of children residing in the household. We based our model on survey data taken by the U.S. Department of Agriculture and the Singaporean government, which showed that higher income, younger in age, and multiple children were the biggest risk factors for high food waste.

After developing our algorithm we implemented it using Java, and created a program that can be used to predict the amount of waste a household is expected to generate.

The last section of the problem brought this issue to our own communities. We had to determine the optimal strategy for maximizing the amount of repurposable food with the minimal cost. We chose to focus on Worcester County. We proposed to repurpose food from grocery stores, hotels/restaurants, and schools to feed those with food insecurity. To quantify the success of our strategy, we determined the total government cost to execute our strategy and to execute the current strategy of food stamps, food waste disposal, and hospital costs. Our strategy proved to minimize the current government cost by 46.9% and use the maximum amount of repurposable food possible.

Team 10933 2 Assumptions for All Problems 1. Data taken from our sources is accurate. a. Justification: Our models are heavily dependent on data, therefore we had to accept data from external sources as true in order to carry out our calculations. 2. All food we choose to distribute is safe and will not harm consumers. a. Justification: We already account for perishable commodities in our model, therefore it is both unpredictable and unreasonable to try and predict whether non-perishables will be safe. 3. Those who are food-insecure are malnourished. a. Justification: The likelihood that a food-insecure person would be malnourished is high, given that they do not always get a healthy number of calories, and although not all food-insecure individuals are malnourished, the generalization simplifies calculations of expenses.

4. Populations increase at a steady rate, so they are predictable. a. Justification: Population data was used to make predictions. It is assumed that population grows at a steady rate, so all predictions remain credible. Definitions for All Problems 1. Children: A person between the ages of 0-18. 2. Food lost: Food items that are no longer in good condition and cannot be redistributed. 3. Food waste: Food items are that are thrown away while still in good condition. 4. Repurposable food: Food that has been considered to be food waste but can be salvaged and given to those with food insecurity 5.

Primary Household Provider: the main income provider and head adult in the family, as determined by the US census.

Problem 1 - Just Eat It! Problem Restatement The goal of this mathematical model is to determine whether the wasted food of a specific state is sufficient enough to nourish its food-insecure population. The state of Texas was used to justify this model. In 2016, a total of \$160 million worth of food was wasted in the United States (Chandler, 2016). Four percent of all meat, nine percent of all fish and seafood, and less than one percent of all milk sold were wasted at the retail level (“​Consumer Behavior Based on Income”, 2016​), and eleven percent of all meat, thirty three percent of all fish and seafood, and fifteen percent of all milk products were wasted at the consumer level (“​Consumer Behavior Based on Income”, 2016)​.

The population of Texas in 2011, 2016, and 2015, were

Team 10933 3 25,657,477, 26,956,958, and 26,956,958 respectively (Wolfram Alpha, 2018). In addition, the population of the United States in 2011 was 313,232,044, while the population of the country in 2016 was 328,677,531. In 2015, the average cost of a meal in Texas was \$2.59 (“Map the Meal Gap 2017: Child Food Insecurity in Texas By County,” 2017). Assumptions and Justifications 1. The correlation between the United States’ population and the amount of food wasted in the United States is linear.

a. Justification: As the population increases throughout the years, the demand for food will increase as well if the food price remains fairly constant.

2. The correlation between the population of a specified area and the amount of food waste each year is linear. a. Justification: As an area’s population increases throughout the years, the demand for food will increase as well if the food price remains fairly constant. 3. The food price remained fairly constant between 2008 and 2017. a. Justification: In past decade, no major event in the United States caused a significant fluctuation in food prices.

4. Data provided by Mathworks Math Modeling Challenge is accurate. a. Justification: The data provided originated from reputable sources on the internet. 5. All outlets and consumers are willing to donate their surplus food. a. Justification: In this theoretical model, we focused on determining whether the surplus food within a state would satisfy the needs of all food-insecure people, and did not waste time or resources determining whether people would be willing to donate food. 6. An outlet’s total food worth is equivalent to the sum of the worth of their wasted product and the worth of their sold items.

a. Justification: At most food distribution centers, the food products are either sold or throw away. Although some supermarkets, like Trader Joe’s, donate a fair amount of their surplus to charities, their contributions are miniscule when compared to the total amount of food wasted in the United States, making these efforts negligible. 7. Three meals, with an average cost of \$2.59 each, is sufficient for all members of the population. a. Justification: It is recommended for an average human to consume three meals a week. It is also specified the average price for each meal in Texas costs \$2.59.

8. Any products that have been destroyed in manufacturing or have gone bad on farms cannot be redistributed to the public and are unavoidably wasted. a. Justification: Products that have gone bad or have been destroyed cannot be redistributed due to health concerns.

Team 10933 4 9. The distributions of food waste in Australia, Canada, New Zealand, and USA are fairly similar. a. Justification: The four countries mentioned above have similar economic situations and their food consumptions are essentially identical. 10. The \$160 million worth of food waste was generated at the retail and consumer level. a. Justification: Food is thrown away by outlets and consumers if it fails to meet an aesthetic threshold or has passed an expiration date. Methodology To begin, we attempted to develop a model using the data from Texas, and then worked backwards to replace the Texas data with variables in order to create a country-wide model.

In order to determine the sum of money wasted on food in a specific state, we researched the total amount of money wasted on food by producers and consumers. Since the only statistic we were able to find was from 2008, we converted the number into a projected value for 2016, assuming that the increase in food wasting will increase in proportion to population of the United States. We set up a proportion with the total amount of money wasted on food in 2008 over the total population in 2008, and set that equal to a variable , or the projected total amount of money mUS wasted on food in 2016, over the population in 2016.

= \$1.656 10 * 11 3.05 10 people * 8 mUS 3.29 10 people * 8 After we found the projected total amount of money in the US wasted on food in 2016, we set up a second proportion in order to scale this number down to the population of Texas. The right side of the previous equation was set equal to a variable , over the population of Texas mT in 2016. The variable represented the total amount of money wasted by both consumers and mT producers in Texas. = 3.29 10 people * 8 \$181,888,524,590 mT 2.786 10 people * 7 After we found the total amount of money wasted by producers and consumers in Texas due to wasting food, we decided that the meat, fish and seafood, and milk products needed further consideration.

The majority of the time, these products are not eaten because they have gone bad, marking them as uncontrollably wasted products that should be removed from the model. In order to remove these products, we used the Consumer Behavior Excel sheet provided in the problem statement to find the mean annual spending on these products by the average consumer. Since there was no date provided on this sheet, we assumed these rates remain fairly constant. We also utilized the 2011 estimated percent of consumer and outlet food products that will be wasted. These percents were converted to projected 2016 percents based off the assumption that they remain proportional to the population.

Team 10933 5 First, the amount of meat, fish and seafood, and milk products wasted by consumers was calculated using proportions. The percents of products projected to be wasted were converted to a proportion of the population in 2016 . p ) ( c = 0.11 3.13 10 people * 8 pc 3.29 10 people * 8 The mean annual spending by the average consumer for each product was then retrieved from the Excel sheet provided in the problem statement and multiplied by each of the corresponding “new percents” to find the total amount of money lost in wasted food per p ) ( c consumer. These numbers were multiplied by the population of Texas and added together to find the total value of the wasted perishable products by consumers.

Next, the value of the wasted perishable products by outlets was calculated using a self-derived formula based on our knowledge of the total amount of money spent by outlets. The amount of money wasted by outlets should equal the total amount of money spent multiplied by the percent that we predicted to be wasted. The total amount of money spent by outlets should equal the total amount of consumer money plus the the amount of wasted food by outlets, since the consumers purchase the products and the products left are thrown away or wasted. Using the variable w to represent the monetary amount of wasted food by outlets, to represent the percent of food wasted by po outlets proportional to the 2016 Texas population, and to represent the total money spent on tc these perishable products, the following equation was created: (w ) w = po + tc w p t w = po + o c 1 )w t ( − po = po c w = p t o c (1−p ) o These values were multiplied by the population in Texas and added together to get the total value of perishable food wasted by outlets in Texas.

The total value of perishable food wasted by consumers in Texas was added to the total value of perishable food wasted by outlets in Texas. This value represents the total value the of perishable food wasted by consumers and outlets. This value was then subtracted by the total value of all food wasted by both consumers and outlets in Texas to achieve the final value of the total amount of redistributable food wasted by consumers and outlets.

Team 10933 6 Table 1: The Calculations of the Total Value of Consumer and Producer Food Wasted Annually Customer Food Annual Consumer Money Spent (\$) Consumer Percent Wasted (%) Producer Percent Wasted (%) Consumer Money Wasted (\$) Total Money Wasted by Texas Consumers Wasted Producer Total Money Wasted by Texas Producers Meat 551.000 0.116 0.042 63.708 1774912534.824 24.183 673750392.209 Fish and Seafood 130.000 0.347 0.095 45.093 1256290178.914 13.583 378423719.962 Milk 410.000 0.158 0.005 64.644 1800975431.310 2.166 60349687.656 Total 4832178145.048 1112523799.827 Total Value of Consumer and Producer Food Wasted 5944701944.875 Finally, the total amount of money required to feed all people in Texas who are food insecure was calculated using existing data from the Feeding America website.

The average cost per meal in Texas in 2015, \$2.59, was converted to be proportional with 2016 data using proportions similar to the conversions of the percents from above. The projected 2016 average cost per meal was multiplied by 3, assuming people eat 3 meals per day, to represent the total cost of food for one person for one day. This value was multiplied by the total number of people in Texas that qualify as food-insecure, as determined by 2015 data adjusted to be proportional to the 2016 population, and then multiplied by 365 days in a year to represent the total amount of money required to feed all food-insecure people in Texas for an entire year.

The total value of the amount of redistributable food wasted annually by private consumers and outlets in Texas was compared to the total amount of money required to feed all food-insecure people residing in Texas. Since the value of food wasted was larger than the amount of money required to feed the food-insecure people, Texas was determined to have the ability to supply the food-insecure population with the food that would have been wasted. The final algorithm, using variable P as the state population, C as the cost per meal, and F as the number of food-insecure people, can be used with any state’s data.

Total value of food wasted by consumers and outlets per year ( : ) V w ( ( 63.708*P)+(45.093*P)+(64.644*P)+(24.183*P)+(13.583*P)+(2.166*P)) V w (3.29 10 ) * 8 (1.786 10 ) P * 11 * -213.378*P V w = (3.29 10 ) * 8 (1.786 10 ) P * 11 * 329.573P V w =

Team 10933 7 This equation was then compared with an equation that could be used to determine the cost of feeding all food-insecure people in a state in a single year. Total cost to feed all food-insecure people for one year ( ): V f = C*3*F*365 V f =1080FC V f If is larger than , the state can be declared able to feed all food-insecure people V w V f with their yearly wasted food. If not, the state has too many food-insecure people to feed using just the food generated by waste. Weaknesses Despite the large profit gained from recycling all food wastage, this model portrays an ideal situation where no amount of food is wasted.

In other words, the model does not account for corporations or consumers who would be unwilling to donate their surplus food. However, due to the large sum of money left over, the \$2,763,459,004.67 provides much leeway with which to fix this particular problem. Another possible weakness is that throughout the calculations, population growth and food wastage were assumed to be proportional. Therefore, the model might be susceptible to extrapolation errors.

Strengths Our model takes into account the fluctuation of population and food wastage. Furthermore, the model examines the two major stages of food waste which are situated at the consumer and retail level. Additionally, it will allow food-insecure citizens to obtain three full meals a day without any added expense to the state. The model is also fairly easy to comprehend and to obtain a result. Therefore, it would be accessible to those who do not have much expertise in the field of mathematical modeling.

Results Replacing the state population, average cost per meal, and number of people that can be classified as food-insecure with values specific to the state of Texas, the state of Texas was determined to have enough wasted food to feed all food-insecure people in 2016.

According to our model, the total amount of money required to feed all food-insecure people of Texas would be \$12,639,016,056, and the total value of all redistributable food wasted by consumers and outlets in Texas would be \$15,402,475,061. The value of food wasted is much larger than the value of meals for food-insecure people, leaving \$2,763,459,004.67 leftover for extra spending.

Team 10933 8 Problem 2 - Food Foolish? Problem Restatement In the second aspect of the problem, we were tasked with creating a model that would determine how much food a household was likely to waste, based on personal choices, traits, and habits. We then needed to show the effectiveness of our model by testing it on four different types of households: a single parent with a toddler and an income of \$20,500; a family of four with an income of \$135,000; an elderly, retired couple with an income of \$55,000; and a single 23 year old with an income of \$45,000.

Assumptions and Justifications 1.

The age of the primary household provider, the income of the household, and the number of children living in the household are the only factors that will impact the amount of food waste a household produces. a. Justification: This is based off information from the USDA and an Electrolux study conducted in 2015 in Singapore that demonstrates that age, income, and children are the largest factors in determining food waste (“2015 Electrolux Food Waste at Home Study,” 2015, ​“Food Wasting Habits May Depend on Age and Gender,” 2018​).

2. The presence of children in the household supersedes the income of the household in order of impactfulness on food waste, and both income and the presence of children supersede the age of the primary household provider in order of impactfulness. a. Justification: This is based off the 2015 Electrolux Food Waste at Home study (“2015 Electrolux Food Waste at Home Study,” 2015). 3. A single parent household will waste as much as a two parent household of the same income and with the same number of children.

a. Justification: Income and number of children supersede any other considerations, including the number of parents living within the household (“2015 Electrolux Food Waste at Home Study,” 2015).

4. Children produce the most food waste in a household. a. Justification: This is due to the tendency of children to be picky and temperamental eaters (“Picky Eaters.”). 5. Children from zero to eighteen have the same propensity for food waste. a. Justification: Even though a young child is more likely to waste food than a teenager, we assumed that all children, regardless of age, would waste the same amount of food for the purposes of creating this model (“Analyzing Food Insecurity in Worcester,” 2012).

Team 10933 9 6. Data related to food waste from Singapore can be used to determine food waste in the United States. a. Singapore is financially comparable to the United States (“U.S. Relations With Singapore,” 2017). Methodology According to the USDA and the 2015 Electrolux Food Waste at Home study, the age of the primary household provider, the income of the household, and the presence of children within the household are the largest factors that can be used to determine whether a household will waste food. Younger individuals, typically under the age of thirty, tend to waste more than their older counterparts .

Lower income households waste less food than higher income households, due to the greater importance of small amounts of food to the overall health of the household, and the greater impact small amounts of food will have in smaller paychecks. Households with children tend to waste more food than households on the same income level that lack children, due to children’s tendency towards picky eating. These data sets also show that having children is the largest impactor on the amount of waste of a household, followed by income, and age of the household’s occupants (“2015 Electrolux Food Waste at Home Study,” 2015).

Due to the limited amount of time in which to complete the problem, instead of focusing on determining the quantitative amount of food wasted, we focused on determining the qualitative amount of food wasted. This qualitative amount was broken down into five categories: low waste, medium low waste, medium waste, medium high waste, and high waste. Using the data found and described above, we developed an algorithm in order to determine the amount of food waste different types of households produce each year. ​We divided income into four categories: 30 thousand or less, between 30 thousand and 50 thousand, between fifty thousand and 100 thousand, and greater than 100 thousand (“United States Census Bureau”, 2010).

​We then divided each of these income categories into the number of people in the household, either a single person or two or more people. For the single person, we divided them up into ages: thirty and under, between thirty and fifty, and fifty and over. If a person belonged to a household with multiple people, we separated them into households without children or households with children. Households without children were categorized along with the same ages as the single-occupant houses. Households with children were categorized according to how many children resided in the house: a single child, two children, or three or more children.

Once we developed this algorithm, we implemented it using Java and obtained how much food waste the households mentioned above would be likely to generate.

A user of the Java program we created will first be asked to input the income of the household under consideration. They will then be asked to input how many occupants live in the household. If the user tells the program that only a single person lives in the household, they will

Team 10933 10 be asked the age of the occupant. From that information, the program determines how much food waste the house is likely to be producing. If the user tells the program that two or more people reside within the household, they will then be asked the age of the primary household provider, and the number of children who reside within the house.

If the number of children is zero, the program will determine the food waste based on the age of the primary household provider and the household’s income. If children reside in the household, the program will determine the food waste based on the number of children and the household’s income.

Figure 1: How data was determined within the algorithm Weaknesses This model’s biggest restrictions come from the limited number of variables used in the model. Our model only takes into account the number of children in the household, the age of the primary household provider, and the income of the household. While these were determined to be the most important factors that can be used to predict a house’s food waste, they are by no means the only factors. Many other factors are intangible and difficult to be accurately quantified or measured, such as a person’s schedule, their diet, or their own opinions on food waste.

If we had access to this type of intangible data, we would incorporate it into our algorithm, and therefore improve its accuracy.

Strengths Each aspect of this model is based off of data from a comprehensive study on food waste habits in various households conducted in Singapore. According to the US Department of State,

Team 10933 11 Singapore and the United States are financially comparable (“U.S. Relations With Singapore,” 2017), and therefore our model is supported by and founded upon strong data. Our model can account for any combination of age, income level, and number of children within a household in order to determine the likely level of waste the household is likely to dispense.

Due to the fact that we implemented our model using Java, anyone wishing to figure out how much waste their household is likely to generate can easily use it. This usability adds to the overall strength of our model.

Results A single parent with a toddler and an annual income of \$20,500 will have a medium low amount of waste. A family of four, with two parents, two teenage children, and an annual income of \$135,000 will have a high amount of waste. A retired couple, with an income of \$55,000 will have a medium low amount of waste. A single 23 year old with an income of \$45,000 will have a medium amount of waste. Table 2: Likely groups for each waste category Waste Category Likely Populations Low Waste 1. Income less than 30k, no children, above the age of fifty Medium Low Waste 1. Income between 50k and 100k, no children, above the age of fifty 2.

Income between 30k and 50k, no children, above the age of fifty 3. Income less than 30k, no children, under the age of thirty Medium Waste 1. Income between 30k and 50k, no children, under the age of fifty 2. Income less than 30k, one child 3. Income less than 30k, no children, under the age of thirty Medium High Waste 1. Income greater than 100k, no children, above the age of fifty 2. Income between 50k and 100k, one child 3. Income between 50k and 100k, no children, between the ages of thirty and fifty 4. Income between 30k and 50k, one or two children 5. Income less than 30k, two or more children High Waste 1.

Income greater than 100k, any number of children 2. Income greater than 100k, no children, under the age of fifty 3. Income between 50k and 100k, two or more children 4. Income between 50k and 100k, no children, under the age of thirty 5. Income between 30k and 50k, three of more children

Team 10933 12 Problem 3 - Hunger Game Plan? Problem Restatement In problem three, we were tasked to bring our model at a smaller scale with a community that we were familiar with, and to determine the optimal strategy in order to maximize the amount of food repurposed with minimal government cost. We chose Worcester County in Massachusetts as our community to aid with food-insecurity. We decided to quantify the benefits of our program based on the following criteria: 1. SNAP’s (Supplemental Nutrition Assistance Program) food stamps (\$4 per day per person) 2. Cost to provide healthcare for the malnourished (a result of food-insecurity) 3.

Cost of transportation from grocery stores to distribution centers 4. Cost of disposing food that cannot/is not repurposed Success was quantified by the percentage increase in people fed and the percentage decrease in the overall cost. A 30% increase and decrease respectively meant that our model was effective. Assumptions and Justifications 1. Worcester County is a fair representation of Massachusetts, therefore percentages of food wasted in grocery stores, schools, and hotels/restaurants in Massachusetts are mirrored in Worcester County.

a. Justification: Worcester County makes up roughly 1/3 of Massachusetts and holds enough people, food pantries, and food suppliers to provide an accurate representation of the state. Because county data is not available for all our necessary calculations, state data had to be converted. 2. Gas prices for delivery are negligible/unaccounted for because stores are in close proximity to food distributors. a. Justification: In most counties, there are plenty of food pantries and grocery stores available, so it can be assumed true that, on average, there is a food pantry close enough to a grocery store that it will not significantly affect gas.

3. The food is packaged in a way where volume does not matter. a. Justification: It would be unreasonable in the time period that we are given, to individually account for the volume of each type of item that is being transported, given the variance.

4. Truck driver salary accounts for the cost of both the truck and truck driver. a. Justification: When a truck driver is hired to transport food, it is assumed that all truck expenses are covered for in his/her salary. 5. Food lost during the manufacturing process is not wasted and unrecoverable.

Team 10933 13 a. This food was never delivered to the general public, and it was not even given the option to be eaten versus wasted. Most of the food lost in this stage is in the manufacturing plant where redistribution is not a viable option. 6. Everyone can survive on 3 lbs of food per day, regardless of their age or other demographics.

a. This average was established using guidelines from sources that state that the average person eats 3 lbs a day, to provide a base for a redistribution strategy (Andrews). It was assumed that when data from all citizens were averaged, the online data would be representative of the population. 7. Homeless people who live in shelters are not among the food-insecure. a. We are assuming that homeless shelters take care of all of their residents’ needs, including food. Therefore, we do not need to consider homeless shelters in our plan to distribute repurposed food.

8. Government sustains food distributors solely through SNAPs a. SNAPs (food stamps) are consistent throughout counties and food pantries, therefore the prices that are given to us can be used in calculations. Government grants vary between food pantries, and some are not government supported at all through grants, therefore it would not be a very accurate indicator of price. The undercompensation will not be harmful to our model, but if we took grants into compensation, we would risk overcompensation.

Methodology To determine the cost that the government spends on food-stamps in Worcester County, we used data from 2015 which documented that 79,390 people in Worcester County are food-insecure individuals.

According to the site, 68% of these people are eligible for SNAP, which is approximately 53,985 people (“Food Insecurity in Worcester County,” 2015). The government provides each of these people with a food-stamp worth \$4 per day (​“The Truth About Food Stamps”​). Therefore, annually, it costs the government \$215,940 daily to feed the people with SNAP, and \$78,818,100 annually.

Next, we determined how much malnutrition healthcare and hospital visits would cost the government. Malnutrition costs hospitals approximately 20% more because patients are readmitted more often and tend to experience longer hospital stays. Each state spends about \$862.5 million on malnutrition healthcare annually (Castellucci, 2016). Proportion A: \$862.5 million 702,630 malnourished MA = \$A 79,390 malnourished MA spent on healthcare for the malnourished 9, 45, 70 A = \$ 7 3

Team 10933 14 Assuming that those who are food insecure are malnourished, a proportion was created to determine the cost for malnourished patients in Worcester County annually.

When the proportion was solved, the cost totaled \$9,745,370. Then, we determined how much it would cost to dispose of food waste to landfills in Worcester County. It costs the United States \$160 billion to dispose of 60 million tons of food waste annually (Chandler, 2016). Using the Massachusetts Commercial/Institutional Food Waste Generation Data for the year 2012, we determined that Massachusetts wasted 947,916 tons of food yearly(“Supplemental Nutrition Assistance Program Participation and Cost Data”). However, we ultimately wanted to find the amount of food wasted in Worcester County in the most recent year with data available--2016.

To do so, statistics were taken from Wolfram Alpha to determine Massachusetts’ and Worcester County’s populations in 2012: ~6,658,000 residents and ~806,313 residents respectively (Wolfram Alpha, 2018). The most recent population data available for WC was the 2016 census, so our calculations were based off of projections for 2016. We began with creating a proportion to estimate how much food was wasted in WC in 2012.

Proportion B: 947,916 tons 6,658,000 people MA = B tons 806,313 people WC wasted by Worcester County (2012) 14, 97 tons B = 1 7 Next, we compared the 2012 data to the most recent census data from Worcester County (2016) to make a more accurate prediction of the number of pounds wasted. According to the data we found, there were 819,589 residents in WC as of 2016 (Massachusetts Population, 2018). Proportion C: 806,313 2012 WC 114, 797 tons 2012 = C tons 2016 819,589 2016 WC wasted by Worcester County (2016) 16, 87 tons C = 1 6 This number was used to determine the cost to dispose of this food waste in a proportion against how much it costs the United States to dispose of their waste.

Proportion D: \$D WC 116,687 tons WC = \$160 billion US 60 million tons US wasted by Worcester County (2016) 311, 65, 00 D = \$ 1 0 The current cost to dispose of Worcester County’s food waste totaled \$311,165,000. Therefore, the total amount that the government spends currently with this food insecurity program totals \$399,728,470.

The next step was to determine whether the program we proposed would decrease the food insecurity rate by repurposing the most amount of food possible at minimal cost. Repurposing the food would limit disposal costs incredibly. To repurpose the most food, we determined the food that had no absolute way to be repurposed without endangering consumers. Then we would remove it from the total food waste and repurpose the remaining food.

Team 10933 15 When determining how much of the food could be repurposed for the food insecure, we removed the meat, fish, and dairy using percentages of those items in stores given (Gustavsson) because those items spoil easily and are more prone to bacteria, making consumers sick.

The percentages are found below, and they were totalled and subtracted from each category. 1. Meat: 4.0% 2. Fish: 9.0% 3. Milk/Dairy: 0.05% We decided to repurpose food from restaurants, supermarkets, wholesale distributors, schools, and hotels because that food would most likely be viable. Table 3: A table depicting the amount of total food wasted in Massachusetts by business and location. We only used the estimated total per year and the percent total per generation (Summary, 2011). Table 4: A table depicting the amount of food wasted but not completely lost and the amount of repurposable food in Massachusetts by certain kinds of businesses (Summary, 2011).

Category Annual Tons of Food Wasted (not Lost) in MA Annual Tons of Food Wasted That Could be Repurposed in MA Restaurants 164,819.0 90,692.3 Supermarkets and Grocery Stores 104,244.0 142,568.0 Wholesale Distributors 73,500.0 63,577.5 Colleges/Universities 19,228.0 19,228.0 Resorts/Conference Facilities 5,792.0 5,792.0 Independent Schools 627.0 627.0 Total 368,210 tons 322,485 tons

Team 10933 16 Using the total tons of food that could be repurposed in MA (see highlighted cell in Table 3), we set up a proportion to solve for how many tons of food could be repurposed in Worcester County itself.

The tons of food were compared to county and state population once again, because we assumed that Worcester County was a fair representation of Massachusetts and that food waste correlates with population. We used the 2012 population statistics because the data from the table was taken from 2012 data.

Proportion E: 322,485 tons 6,658,000 MA = E tons 806,313 WC of food that can be repurposed in Worcester County (2012) 9, 54.3 tons E = 3 0 Converting to data from 2016 for a more accurate prediction, Proportion F​: 39,054.3 tons 806,313 people = F tons 819,589 people of food that could be repurposed in Worcester County (2016) 9, 97.4 tons F = 3 6 We then converted the tons of food wasted annually in Worcester County that can be redistributed into pounds by multiplying our number ​T​ by a factor of 2000, and divided it by 365 to get the amount of lbs of food we can redistribute per day (217520 lbs/day).

Proportion G: G people 217520 lbs = 3 lbs 1 person individuals who can be fed 3 lbs of food a day 2, 07 G = 7 5 On average, Americans eat 3-5 lbs a day (Andrews). Therefore, if we provided them with 3 lbs of food a day, that would feed 72,507 people per day. Compared to the current 79,390 food-insecure individuals, the repurposing of food would decrease that number by 91.33%--an incredible ​difference.

To make this system happen, the food would need to be shipped from grocery stores and restaurants to nearby shelters and food pantries. To obtain minimal cost for this system, it would be ideal for volunteers to help transport food items to those in need, for no cost. However, since this is unlikely, we calculated the cost to hire trucks to distribute the food, the cost to dispose of the food that cannot be repurposed, and the cost to feed the remaining people not covered by this program. Theoretically, malnutrition would be solved by repurposing the food, so those costs would not need to be accounted for.

There would need to be 39,054.3 tons of food that need to be distributed annually (107.0 tons daily), according to calculations above. Based on statistics, the average truck can hold 43,000 lbs, or 21.5 tons (“Truck Driver Salary”). There would need to be 5 trucks hired per year,

Team 10933 17 which each drive and distribute food daily. The cost to hire a singular truck is \$43,464, which totals \$217,320 annually. The next step is to determine the cost of disposing of food that cannot be repurposed, which includes food from manufacturers and meat, dairy, and fish removed from waste from grocery stores, restaurants, and hotels.

According to a study done in MA in 2011 , the amount of annual wasted food in Massachusetts is 625,431 tons, when accounting for the amount of food being repurposed, shown in Table 2 (Summary, 2011).

Proportion H: 625,431 tons 6,658,000 people MA = H tons 806,313 people WC tons of food that cannot be repurposed in Worcester County 5, 42.4 H = 7 7 The above proportion was used to determine the the amount of food that cannot be repurposed in Worcester County by comparing the completely wasted food in MA with the MA population population and the Worcester County population. The result was 75,742.4 tons of food that cannot be repurposed in Worcester County. The cost to dispose of this was determined with the proportion below, and it was \$201,980,000.

Proportion I: \$I WC 75,742.4 tons = 60 million tons \$160 billion US to dispose of the non-repurposable food 201, 80, 00 I = \$ 9 0 Lastly, we determined the cost it would take to feed those who are not covered by this program because this program is projected to feed 72,507 people, when there are 79,390 people with food insecurity in Worcester County.

With this program, 6,883 people would need to be fed with SNAP. SNAP provides \$4 to each person per day, as mentioned previously. This totals to a cost of \$10,049,180. Therefore, with our implemented program, the government cost would total \$212,246,000 This is \$187,482,000 less than the current program, and a 46.9% decrease from the original price, which was \$399,728,470.

Weaknesses The weaknesses for this model fell in its numerous assumptions. Since there was limited data available for Worcester County on food waste which forced us to approximate with proportions, the costs, amounts of food, etc., may not be entirely accurate to Worcester County. The model also does not take into account the price of gas to drive the food trucks. The cost to package food to send to those with food insecurity and the cost to check food safety were unaccounted for. The model also assumed that all food waste produced by manufacturers was unsalvageable for consumption, when in reality it could possibly contribute to the repurposable food to feed those with food insecurity.

Another weakness that the model has is that it does not account for the fact that people of different ages require different kinds of food in different

Team 10933 18 quantities. Lastly, the model assumes that there will be no malnutrition hospital costs after this program is implemented, when reality that is unavoidable, especially since some people with malnutrition do not necessarily have food insecurity. Strengths Our method is ideal for repurposing food with minimal costs because it takes into account a worst-case scenario where every single person we cannot feed with our repurposing plan will be supported with SNAPs. In reality, only around 68% percentage of this population is eligible for SNAPs, and the rest of the food-insecure would have to pay from their own wallets.

We made the generalization because there was no way for us to determine which citizens would receive the repurposed meals. We also did not take into account government grants set aside for the purpose of food distribution which would fund additional parts of our program. Therefore, by overestimating costs, we ensure that our costs meet our goal of decreasing governmental expenditures by at least 30%. Finally, our model is proportion based, and therefore, it is very flexible with changes in data, because it would only change terms during multiplication. Results Table 5: The final comparisons show that our plan minimizes cost in every area except transportation, and that the total cost is much lower.

Current Plan (Worcester County) Repurposed Distribution Plan (Worcester County) \$78,818,100 for SNAPs \$10,049,180 for SNAP's \$9,745,370 for malnourished patients Negligible for malnourished patients (everyone will be fed through SNAP or repurposed meals) \$311,165,000 to dispose of food \$201,980,000 to dispose of food Negligible for transportation because the food is being discarded instead \$217,320 for transportation via truck Total: \$399,728,470 Total: \$212,246,000 Our implemented program would total \$212,246,000 in government costs, \$187,482,000 less than the current program, which costs \$399,728,470.

This is a 46.9% decrease from the original price. Our program distributed\s maximum repurposable food to those in need by removing the unsalvageable/unsafe food from the total amount of food waste, and saving all the rest. The program would cost minimally with the help of volunteers running the program to transport food. However, because we cannot rely on volunteers, the cost for this program accounted for the cost to hire people to transport food, and it still minimized food insecurity in Worcester County by 91.33% at minimal cost.

Team 10933 19 Conclusion The amount of food waste in the United States is steadily increasing, and there are many effective uses for unwanted food besides letting it go to waste. In all three problems, the prevalence of excessive food waste was brought to our attention, and we have found alternative ways of repurposing this food. In problem one, it was shown that the food that normally goes to waste in households and food distributing places, can be used to feed the portion of the population considered to be food-insecure. In problem two, the factors that commonly contribute to excessive food waste were analyzed, and it was shown that a person’s age, income, and children had a profound effect on the amount of household waste.

In problem three, effective methods of waste-reduction and food repurposing were explored, and it was found that repurposing food had the potential to greatly decrease the number of food-insecure individuals in our community, as well as reduce government costs associated with supporting those with food insecurities. The issues of hunger and food waste have both become threats in many states, and this problem has allowed us to explore the unique opportunities for communities to save their neighbors from starvation by repurposing existing waste production, therefore solving two problems in a single action.

Team 10933 20 Works Cited “2015 Electrolux Food Waste at Home Study.” ​Zero Waste Singapore. ​Retrieved from http://www.zerowastesg.com/tag/2015-electrolux-food-waste-at-home-survey/. Allen, D., Filice, J., Patel, N., and Warner, B. “Analyzing Food Security in Worcester.” Worcester Polytechnic Institute. ​15 May 2012. Retrieved from https://web.wpi.edu/Pubs/E-project/Available/E-project-043012-090858/unrest ricted/IQP _Final_Paper.pdf. Andrews, R. “What are Your Four Pounds Made of?” ​PrecisionNutrition. ​Retrieved from https://www.precisionnutrition.com/what-are-your-4-lbs Castellucci, M.

“Malnutrition Causes \$15.5 Billion in Healthcare Spending Per Year.” ​Modern Healthcare. ​23 Sept 2016. Retrieved from http://www.modernhealthcare.com/article/20160923/NEWS/160929940. Chandler, A. “Why Americans Lead the World in Food Waste.” ​The Atlantic. ​15 July 2016. Retrieved from https://www.theatlantic.com/business/archive/2016/07/american-food-waste/49 1513/. “Consumer Behavior Based on Income.” ​Consumer Expenditure Survey. ​2016. Retrieved from https://m3challenge.siam.org/node/385.

“Food Insecurity in Worcester County.” ​Feeding America. ​2015. Retrieved from http://map.feedingamerica.org/county/2015/overall/massachusetts/county/worc ester. Francoeur, L. “How Much Freight Fits on a Full Truckload?” ​XTL Transport Logistics Division. 10 Nov 2014. Retrieved from ​http://www.xtl.com/much-freight-fits-full-truckload/. Gustavsson, J., Cederberg, C., Sonesson, U., Van Otterdijk, R. & Meybeck, A. ​Food and Agriculture Organization of the United Nations. ​2011. Retrieved from http://www.fao.org/docrep/014/mb060e/mb060e00.pdf “Hunger and Poverty Facts.” ​Feeding America. ​Retrieved from http://www.feedingamerica.org/hunger-in-america/hunger-and-poverty-facts.ht ml.

“Map the Meal Gap 2017: Child Food Insecurity in Texas By County.” ​Feeding America. Retrieved from http://www.feedingamerica.org/research/map-the-meal-gap/2015/MMG_AllCountie s_C Ds_CFI_2015_2/TX_AllCounties_CDs_CFI_2015.pdf.

Massachusetts Population. (2018-01-19). Retrieved 2018-03-04, from http://worldpopulationreview.com/states/massachusetts-population/. Mendoza, D. “Food Wasting Habits May Depend on Age and Gender.” ​Today Online. ​4 March 2018. Retrieved from https://www.todayonline.com/lifestyle/food/food-wasting-habits-may-depend-a ge-and-ge nder.

Team 10933 21 “Picky Eaters.” ​UCSF Benioff Children’s Hospital. ​Retrieved from https://www.ucsfbenioffchildrens.org/education/picky_eaters/. “Summary Analysis of Massachusetts Commercial/Institutional Food Waste Generation Data.” Massachusetts Department of Environmental Protection.

​2011. Retrieved from https://www.mass.gov/files/documents/2016/08/uo/foodsum.pdf. “Supplemental Nutrition Assistance Program Participation and Cost Data.” ​United States Department of Agriculture. ​4 Feb 2018. Retrieved from https://catalog.data.gov/dataset/supplemental-nutrition-assistance-program- participation-a nd-cost-data.

Team 10933 22 Appendix Code for Problem 2 import java.util.Scanner; public class Mathworks { public static void main(String args[]) { System.out.println("Input the income of the household:"); Scanner sc = new Scanner(System.in); int income = sc.nextInt(); if (income 1) { System.out.println("Input the age of the primary household provider:"); Scanner hc = new Scanner(System.in); int ageP = hc.nextInt(); System.out.println("How many children 0-18 live in the household?");

Team 10933 23 int numChild = hc.nextInt(); if (numChild == 0) { if (ageP 30 && ageP 50) { System.out.println("Low Waste"); } } else if (numChild == 1) { System.out.println("Medium Waste"); } else if (numChild == 2) { System.out.println("Medium High Waste"); } else if (numChild >= 3) { System.out.println("Medium High Waste"); } } } else if (income > 30000 && income

Team 10933 24 System.out.println("Medium Waste"); } else if (age > 50) { System.out.println("Medium Low Waste"); } } else if (numPeople > 1) { System.out.println("Input the age of the primary household provider:"); Scanner hc = new Scanner(System.in); int ageP = hc.nextInt(); System.out.println("How many children 0-18 live in the household?"); int numChild = hc.nextInt(); if (numChild == 0) { if (ageP 30 && ageP 50) { System.out.println("Medium Low Waste"); } } else if (numChild == 1) { System.out.println("Medium High Waste"); } else if (numChild == 2) { System.out.println("Medium High Waste"); } else if (numChild >= 3) { System.out.println("High Waste"); } } }

Team 10933 25 else if (income > 50000 && income 1) { System.out.println("Input the age of the primary household provider:"); Scanner hc = new Scanner(System.in); int ageP = hc.nextInt(); System.out.println("How many children 0-18 live in the household?"); int numChild = hc.nextInt(); if (numChild == 0) { if (ageP 30 && ageP 50) { System.out.println("Medium Low Waste");

Team 10933 26 } } else if (numChild == 1) { System.out.println("Medium High Waste"); } else if (numChild == 2) { System.out.println("High Waste"); } else if (numChild >= 3) { System.out.println("High Waste"); } } } else if (income > 100000) { System.out.println("Input the number of people in the household:"); Scanner pc = new Scanner(System.in); int numPeople = pc.nextInt(); if (numPeople == 1) { System.out.println("Input the age of the occupant:"); Scanner ac = new Scanner(System.in); int age = ac.nextInt(); if (age 30 && age 50) { System.out.println("Medium High Waste"); } } else if (numPeople > 1) { System.out.println("Input the age of the primary household provider:"); Scanner hc = new Scanner(System.in); int ageP = hc.nextInt();

Team 10933 27 System.out.println("How many children 0-18 live in the household?"); int numChild = hc.nextInt(); if (numChild == 0) { if (ageP 30 && ageP 50) { System.out.println("Medium High Waste"); } } else if (numChild == 1) { System.out.println("High Waste"); } else if (numChild == 2) { System.out.println("High Waste"); } else if (numChild >= 3) { System.out.println("High Waste"); } } } } }

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