Ismet Buyuktahtakin-Toy

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Career: Dynamic Invasive Species Control Optimization Via Integrated Education And Research (Discover)
Buyuktahtakin-Toy, I.
National Science Foundation
9/6/17 → 2/28/21
Project: Research project

34 Article
5 Paper
4 Conference contribution
1 Comment/debate

COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk
Yin, X., Büyüktahtakın, E. & Patel, B. P., Jan 1 2023, In: European Journal of Operational Research. 304, 1, p. 255-275 21 p.
Research output: Contribution to journal › Article › peer-review
7 Scopus citations
Scenario-dominance to multi-stage stochastic lot-sizing and knapsack problems
Büyüktahtakın, E., May 2023, In: Computers and Operations Research. 153, 106149.
Research output: Contribution to journal › Article › peer-review

Open Access
A simulation-deep reinforcement learning (SiRL) approach for epidemic control optimization
Bushaj, S., Yin, X., Beqiri, A., Andrews, D. & Büyüktahtakın, I. E., 2022, (Accepted/In press) In: Annals of Operations Research.
Research output: Contribution to journal › Article › peer-review

Open Access
2 Scopus citations
Correction to: Stage-t scenario dominance for risk-averse multi-stage stochastic mixed-integer programs (Annals of Operations Research, (2022), 309, 1, (1-35), 10.1007/s10479-021-04388-3)
Büyüktahtakın, I. E., 2022, (Accepted/In press) In: Annals of Operations Research.
Research output: Contribution to journal › Comment/debate › peer-review

Open Access
Predicting the COVID19 Trajectory with a Simulation Deep Reinforcement Learning Approach
Bushaj, S., Büyüktahtakın, E. & Beqiri, A., 2022, IISE Annual Conference and Expo 2022. Ellis, K., Ferrell, W. & Knapp, J. (eds.). Institute of Industrial and Systems Engineers, IISE, (IISE Annual Conference and Expo 2022).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ismet Buyuktahtakin-Toy

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Career: Dynamic Invasive Species Control Optimization Via Integrated Education And Research (Discover)

COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk

Scenario-dominance to multi-stage stochastic lot-sizing and knapsack problems

A simulation-deep reinforcement learning (SiRL) approach for epidemic control optimization

Correction to: Stage-t scenario dominance for risk-averse multi-stage stochastic mixed-integer programs (Annals of Operations Research, (2022), 309, 1, (1-35), 10.1007/s10479-021-04388-3)

Predicting the COVID19 Trajectory with a Simulation Deep Reinforcement Learning Approach

Ismet Buyuktahtakin-Toy

Fingerprint

Network

Projects

Career: Dynamic Invasive Species Control Optimization Via Integrated Education And Research (Discover)

Research output

COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk

Scenario-dominance to multi-stage stochastic lot-sizing and knapsack problems

A simulation-deep reinforcement learning (SiRL) approach for epidemic control optimization

Correction to: Stage-t scenario dominance for risk-averse multi-stage stochastic mixed-integer programs (Annals of Operations Research, (2022), 309, 1, (1-35), 10.1007/s10479-021-04388-3)

Predicting the COVID19 Trajectory with a Simulation Deep Reinforcement Learning Approach