TY - GEN
T1 - Food Bank Responsiveness During Disasters
AU - Idoko, Faith
AU - Davis, Lauren
AU - Vogiatzis, Chrysafis
N1 - Publisher Copyright:
© IISE and Expo 2023.All rights reserved.
PY - 2023
Y1 - 2023
N2 - The unpredictable nature of disasters (caused by natural phenomena or human activity) often leads to supply chain disruptions. In the aftermath of a disaster, disruptions in food supply specifically affect the role of food banks. The increase in number of food insecure people during and after a disaster causes a surge in demand to food banks in the affected areas. Prepositioning relief items to mitigate the effect of disasters has proven to be a viable approach to curb this problem. In this work, we incorporate this concept in building a resilient network system for a non-profit organization while accounting for the distribution of food items. The state of the network, such as road and facility availability post disaster is crucial in managing the flow within the network and estimates based on weather characteristics, operational policies, etc. are made beforehand to enhance preparations. Pop-up delivery options such as mobile pantries or self-accessible food lockers for both frozen and dry food items, are also considered in an attempt to strengthen the relief response. A mixed integer linear programming model is used to propose a robust network structure for the Food Bank of Central and Eastern North Carolina (FBCENC) using the events around hurricane Florence as a case study. Findings from this study can be applied to other food banks or organizations with similar network structure as well as various disaster types.
AB - The unpredictable nature of disasters (caused by natural phenomena or human activity) often leads to supply chain disruptions. In the aftermath of a disaster, disruptions in food supply specifically affect the role of food banks. The increase in number of food insecure people during and after a disaster causes a surge in demand to food banks in the affected areas. Prepositioning relief items to mitigate the effect of disasters has proven to be a viable approach to curb this problem. In this work, we incorporate this concept in building a resilient network system for a non-profit organization while accounting for the distribution of food items. The state of the network, such as road and facility availability post disaster is crucial in managing the flow within the network and estimates based on weather characteristics, operational policies, etc. are made beforehand to enhance preparations. Pop-up delivery options such as mobile pantries or self-accessible food lockers for both frozen and dry food items, are also considered in an attempt to strengthen the relief response. A mixed integer linear programming model is used to propose a robust network structure for the Food Bank of Central and Eastern North Carolina (FBCENC) using the events around hurricane Florence as a case study. Findings from this study can be applied to other food banks or organizations with similar network structure as well as various disaster types.
KW - Disaster
KW - Humanitarian logistics
KW - Hunger relief
KW - Non-profit organization
KW - Supply chain disruptions
UR - http://www.scopus.com/inward/record.url?scp=85174918590&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85174918590&partnerID=8YFLogxK
U2 - 10.21872/2023IISE_2935
DO - 10.21872/2023IISE_2935
M3 - Conference contribution
AN - SCOPUS:85174918590
T3 - IISE Annual Conference and Expo 2023
BT - IISE Annual Conference and Expo 2023
A2 - Babski-Reeves, K.
A2 - Eksioglu, B.
A2 - Hampton, D.
PB - Institute of Industrial and Systems Engineers, IISE
T2 - IISE Annual Conference and Expo 2023
Y2 - 21 May 2023 through 23 May 2023
ER -