Publications
Data Envelopment Analysis Meets Community-Powered Refugee Resettlement
Under review
Fatemeh Farajzadeh, Sarah Stanlick, Vincent Charles, Andrew C. Trapp.
This study evaluates the effectiveness of community-powered teams, known as Neighborhood Support Teams (NSTs), in facilitating the resettlement of refugee families to the United States (US) under humanitarian parole. For the first time, we apply a multi-criteria performance analysis to reveal key drivers of successful refugee integration in host communities pertaining to NST operations. We partner with a regional, multi-state nonprofit in the US to collect data on influencing factors through Community-Based Participatory Research (CBPAR) and apply Data Envelopment Analysis (DEA) on this data to provide actionable recommendations.
Risk-Averse Placement Optimization in Refugee Resettlement
Under review
Fatemeh Farajzadeh, Narges Ahani, Osman Ozaltın, Andrew C. Trapp.
This study delves into the use of analytical modeling for refugee resettlement, focusing on machine learning to predict refugee employment possibilities. By recognizing uncertainties in matching refugees with communities, our approach prioritizes risk from an individual refugee family viewpoint. Through real refugee data, we show that our model effectively reduces employment volatility while ensuring fair opportunities for the most vulnerable refugees. Our findings offer valuable insights for more effective refugee resettlement decisions.
Optimizing Sponsored Humanitarian Parole
EAAMO '23: Equity and Access in Algorithms, Mechanisms, and Optimization
Fatemeh Farajzadeh, Ryan Killea, Alexander Teytelboym, Andrew C. Trapp.
This study is motivated by sponsored humanitarian parole, a recently introduced pathway for relocating refugees to the United States, and the resulting need for a well-designed algorithmic matching process to ensure fairness and efficiency among vulnerable populations. Refugees Matching Through HIAS (RUTH) is a first-of-a-kind algorithmic matching system that is driven by the relocation preferences of refugees and the priorities of US sponsors. The potential of RUTH to improve the efficiency and fairness of rapidly deployed humanitarian parole processes highlights the importance of responsible and ethical algorithmic design to promote equity and access to opportunity. RUTH has been used by HIAS to relocate Ukrainian refugees to the US.
A link to the paper is here.
Optimization for Secure and Humane Border Operations
Encyclopedia of Optimization, 2022.
Fatemeh Farajzadeh, Andrew C. Trapp.
This chapter outlines key borderland operations challenges in location, allocation, and search and rescue operations. Guided by dual humanitarian and security purposes, in conjunction with increasing technological capabilities, operations research and analytics researchers may consider the excellent opportunity to further explore this complex planning environment and underlying optimization challenges.
A link to the book chapter is here. Enjoy reading it!
Scientific Reports, 2022.
Amirhossein Moadab, Fatemeh Farajzadeh, Omid F. Valilai
This paper considers a last-mile delivery system in which a set of drones are operated in coordination with public transportation system to deliver a set of orders to destination points. For the first time, an optimization model rooted in the Vehicle Routing Problem (VRP) is introduced to solve such systems.
A link to the paper is here.
IFAC-PapersOnLine, 2020.
Fatemeh Farajzadeh, Amirhossein Moadab, Omid F. Valilai
This study introduces a new optimization model to optimize drone delivery operations in a multi-echelon supply chain, including third-party logistics providers, warehouses, and consumers, as well as charging stations. The paper presents a conceptual model and proposes a MILP model to mathematically formulate such a complex system.
A link to the paper is here.