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1. Clustering Partner Agencies for a Local Food Bank

   Ivuawuogu, H. ; Jiang, S. ; Davis, L. ( May 2023 , Proceedings of 2023 Industrial and Systems Engineering Annual Conference)

   Babski-Reeves, K. ; Eksioglu, B. ; Hampton, D. (Ed.)

   Food insecurity is a serious problem in America and the pandemic makes the problem even worse. Feeding America has more than 200 food banks. that These food banks and their partner agencies are the key players in the battle against food insecurity. Partner agencies may vary in size and location depending on the service area and the variety of the partner agencies and the complexities of their operations make equitable food distribution very challenging. There is a need for a meaningful to group those partner agencies to assist food bank operations managers to make informed decisions. This study uses data from a local food bank and its partner agencies. Each agency is unique in terms of its behavior. Therefore, k-means clustering was used to categorize agencies into groups based on the number of persons served and the amount of food received. The results of the study will provide evidence-based information to assist the food bank in making informed decisions. 

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2. An Interactive Dashboard to Study the Impact of Hurricane Florence on Food Bank Operations

   https://doi.org/10.1109/CSCI51800.2020.00219  

   Enyew, Bantwale ; Odubela, Kehinde ; Jiang, Steven ; Davis, Lauren ( December 2020 , 2020 International Conference on Computational Science and Computational Intelligence (CSCI))

   null (Ed.)

   North Carolina is the third most hurricane-prone states in the US. In 2018, Hurricane Florence caused a lot of damages to households in North Carolina. The Food Bank of Central and Eastern North Carolina (FBCENC) serves 34 counties in North Carolina, and 22 of them were affected by Hurricane Florence. This research aims to investigate the impact of Hurricane Florence on the operations of FBCENC. We developed interactive dashboards to visualize food bank operational data and other relevant data and studied the trends and patterns of food distribution in three key stages: preparedness, response, and recovery. These dashboards enable food bank operations managers to explore and interact with the data with ease to explore the operational data at different stages, at different branch level, and on a different time scale (monthly, weekly, or daily). The impact on the operations of affected service areas vs. not affected areas could be investigated as well. The findings of this research will provide insight into how humanitarian relief agencies can better prepare for, respond to, and recover from the disruptions caused by hurricanes. 

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3. Joint Optimization of Autonomous Electric Vehicle Fleet Operations and Charging Station Siting

   https://doi.org/10.1109/ITSC48978.2021.9565089  

   Luke, Justin ; Salazar, Mauro ; Rajagopal, Ram ; Pavone, Marco ( September 2021 , 2021 IEEE International Intelligent Transportation Systems Conference (ITSC))

   Charging infrastructure is the coupling link between power and transportation networks, thus determining charging station siting is necessary for planning of power and transportation systems. While previous works have either optimized for charging station siting given historic travel behavior, or optimized fleet routing and charging given an assumed placement of the stations, this paper introduces a linear program that optimizes for station siting and macroscopic fleet operations in a joint fashion. Given an electricity retail rate and a set of travel demand requests, the optimization minimizes total cost for an autonomous EV fleet comprising of travel costs, station procurement costs, fleet procurement costs, and electricity costs, including demand charges. Specifically, the optimization returns the number of charging plugs for each charging rate (e.g., Level 2, DC fast charging) at each candidate location, as well as the optimal routing and charging of the fleet. From a case-study of an electric vehicle fleet operating in San Francisco, our results show that, albeit with range limitations, small EVs with low procurement costs and high energy efficiencies are the most cost-effective in terms of total ownership costs. Furthermore, the optimal siting of charging stations is more spatially distributed than the current siting of stations, consisting mainly of high-power Level 2 AC stations (16.8 kW) with a small share of DC fast charging stations and no standard 7.7kW Level 2 stations. Optimal siting reduces the total costs, empty vehicle travel, and peak charging load by up to 10%. 

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4. Toward a More Diverse and Equitable Food Distribution System: Amplifying Diversity, Equity and Inclusion in Food Bank Operations

   https://doi.org/10.1177/10591478241252691  

   Hamilton, Mikaya ; Morrow, Jr., Benjamin_F ; Davis, Lauren_B ; Morgan, Shona ; Ivy, Julie_S ; Jiang, Steven ; Chi, Min ; Hilliard, Kyle ( May 2024 , Production and Operations Management)

   This article provides an evidence-based discussion of an ongoing effort within the operations of hunger relief organizations to address diversity, equity, and inclusion (DEI) by sourcing and distributing more culturally relevant food. Through nearly 100 interviews with food bank personnel in diverse roles (from partner agency relations to executives) representing various regions of the United States, we explore the challenges faced by different functional units within the organization. These interviews indicate a shift to more inclusive language, more personalized metrics, and more inclusive operations. We critically analyze the related literature and identify opportunities for infusing DEI practices in the study of hunger relief supply chains.

    

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5. Food Aid Agency Survey Instrument:Food Access Impact Survey for Harris County and Southeast Texas after Hurricane Harvey in 2017

   https://doi.org/10.17603/ds2-sqrq-jv57  

   Lane, Gina ; Rosenheim, Nathanael ; Maher, Dan ; Peacock, Walter Gillis ( March 2021 , Designsafe-CI)

   The food aid agency survey design was informed by the focus group discussion and aimed to gain quantitative data from all food aid agencies affiliated or associated with the Southeast Texas Food Bank. A list of affiliated food aid agencies, their managers, and email addresses was obtained from the Southeast Texas Food Bank. The list included the 89 food aid agencies active in Southeast Texas prior to Hurricane Harvey. Each of these food aid agencies was emailed a personalized invitation to the online survey. The survey of food aid agencies was conducted online using the survey software program Qualtrics XM (Qualtrics, 2019). The online surveys integrated data collected from the Southeast Texas Food Bank Primarius system to tailor specific questions to specific food aid agencies. The survey was designed to collect information on (1) physical damage to the food aid agency, disruption or damage to infrastructure, and transportation and access problems; (2) impact on workers or volunteers; and (3) disruptions to operations and inventory, which included changes in the food distribution schedule, food categories distributed, and sources of food.Food insecurity is a chronic problem in the United States that annually affects over 40 million people under normal conditions. This difficult reality can dramatically worsen after disasters. Such events can disrupt both the supply and demand sides of food systems, restricting food distribution and access precisely when households are in a heightened need for food assistance. Often, retailers and food banks must react quickly to meet local needs under difficult post-disaster circumstances. Residents of Harris County and Southeast Texas experienced this problem after Hurricane Harvey made landfall on the Texas Gulf Coast in August 2017. The primary data collected by this project relate specifically to the supply side. The data attempt to identify factors that impacted the ability of suppliers to help ensure access to food, with a focus on fresh food access. Factors included impacts to people, property and products due to hurricane-related damage to infrastructure. Two types of food suppliers were the foci of this research: food aid agencies and food retailers. The research team examined food aid agencies in Southeast Texas with data collection methods that included secondary data analysis, a focus group and an online survey. The second population studied was food retailers with in-person surveys with store managers. Food retailers were randomly sampled in three Texas counties: Jefferson, Orange, and Harris. The data collection methods resulted in 32 food aid agency online survey responses and 210 completed food retail in-person surveys. Data were collected five to eight months after the event, which helped to increase the reliability and validity of the data. The time-sensitive nature of post-disaster data requires research teams to quickly organize their efforts before entering the field. The purpose of this project archive is to share the primary data collected, document methods, and to help future research teams reduce the amount of time needed for project development and reporting. This archive does not contain Personally or Business Identifiable Information. 

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