37 citations · 67 across the 13 of their papers we have counts for
13 papers
On the Optimization of Benefit to Cost Ratios for Public Sector Decision Making
Frederick "Forrest" Miller, Yaren Bilge Kaya, Geri L. Dimas +3
Decision making in the public sector centers on delivering resources and services for the common good, emphasizing an expansive set of objectives such as equity and efficiency, bey…
Discrete Event Simulation to Evaluate Shelter Capacity Expansion Options for LGBTQ+ Homeless Youth
Yaren Bilge Kaya, Sophia Mantell, Kayse Lee Maass +4
The New York City (NYC) youth shelter system provides housing, counseling, and other support services to runaway and homeless youth and young adults (RHY). These resources reduce R…
DiversiTree: A New Method to Efficiently Compute Diverse Sets of Near-Optimal Solutions to Mixed-Integer Optimization Problems
Izuwa Ahanor, Hugh Medal, Andrew C. Trapp
While most methods for solving mixed-integer optimization problems compute a single optimal solution, a diverse set of near-optimal solutions can often lead to improved outcomes. W…
Improving Access to Housing and Supportive Services for Runaway and Homeless Youth: Reducing Vulnerability to Human Trafficking in New York City
Yaren Bilge Kaya, Kayse Lee Maass, Geri L. Dimas +3
Recent estimates indicate that there are over 1 million runaway and homeless youth and young adults (RHY) in the United States (US). Exposure to trauma, violence, and substance abu…
Optimization for Secure and Humane Border Operations
Fatemeh Farajzadeh, Andrew C. Trapp
In 2020 tens of millions of migrants worldwide sought safety due to various push-pull factors such as economic, geographic, demographic, and societal challenges. Large movements of…
Human-Centric Decision Support Tools: Insights from Real-World Design and Implementation
Narges Ahani, Andrew C. Trapp
Decision support tools enable improved decision-making for challenging decision problems by empowering stakeholders to process, analyze, visualize, and otherwise make sense of a va…
Dynamic Placement in Refugee Resettlement
Narges Ahani, Paul Gölz, Ariel D. Procaccia +2
Employment outcomes of resettled refugees depend strongly on where they are placed inside the host country. Each week, a resettlement agency is assigned a batch of refugees by the…
Operations Research and Analytics to Combat Human Trafficking: A Systematic Review of Academic Literature
Geri L. Dimas, Renata A. Konrad, Kayse Lee Maass +1
Human trafficking is a widespread and compound social, economic, and human rights issue occurring in every region of the world. While there have been an increasing number of anti-h…
Estimating Effectiveness of Identifying Human Trafficking via Data Envelopment Analysis
Geri L. Dimas, Malak El Khalkhali, Alex Bender +5
Transit monitoring is a preventative approach used to identify possible cases of human trafficking prior to exploitation while an individual is in transit or before one crosses a b…
Perspectives on How To Conduct Responsible Anti-Human Trafficking Research in Operations and Analytics
Renata Konrad, Kayse Lee Maass, Geri L. Dimas +1
Human trafficking, the commercial exploitation of individuals, is a gross violation of human rights and harms societies, economies, health and development. The related disciplines…
MAP Clustering under the Gaussian Mixture Model via Mixed Integer Nonlinear Optimization
Patrick Flaherty, Pitchaya Wiratchotisatian, Ji Ah Lee +2
We present a global optimization approach for solving the maximum a-posteriori (MAP) clustering problem under the Gaussian mixture model.Our approach can accommodate side constrain…
A Deterministic Global Optimization Method for Variational Inference
Hachem Saddiki, Andrew C. Trapp, Patrick Flaherty
Variational inference methods for latent variable statistical models have gained popularity because they are relatively fast, can handle large data sets, and have deterministic con…
A global optimization algorithm for sparse mixed membership matrix factorization
Fan Zhang, Chuangqi Wang, Andrew Trapp +1
Mixed membership factorization is a popular approach for analyzing data sets that have within-sample heterogeneity. In recent years, several algorithms have been developed for mixe…