Presented at INFORMS Annual Meeting 2023

Created in October 16, 2023

2023

INFORMS 2023 was held on October 15-18, 2023 in Phoenix, AZ. I presented our paper (Sabah Bushaj, Esra Buyuktahtakin Toy, Robert G. Haight) A Risk-Averse Multistage Stochastic Model Utilizing Scenario Dominance Cuts for Optimal Control of a Forest Invasive Insect in the Stochastic Programming with Discrete Decisions and/or Decision-Dependent Uncertainty session in CC-North 224A at 8:00 AM.

Abstract

In this study, we formulate a risk-averse multistage, stochastic, mixed-integer programming (RA-MSS-MIP) model. We then present a cutting plane algorithm based on scenario ordering to tackle decision-dependent uncertainty for an invasive species management problem. We aim to assist decision-makers in allocating resources for the surveillance of the ash population for Emerald Ash Borer (EAB) infestation and subsequent treatment and removal of infested trees over space and time in the State of New Jersey.

My colleague Xuecheng Yin presented our (Xuecheng Yin, Esra Buyuktahtakin Toy, Sabah Bushaj, Yue Yuan) research paper Covid-19: Agent-Based Simulation-Optimization to Vaccine Center Location Vaccine Allocation Problem published in the Breaking the Chain: Leveraging Operations Research to Control and Mitigate Infectious Outbreaks session in CC-West 101A at 2:15 PM.

Abstract

This paper presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, while their integrated utilization focuses on the COVID19 vaccine allocation challenges. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The integrated epidemiological MIP and agent based approach balances the proportion of vaccines distributed to a county with that county’s population in proportion to all counties under different budgets.