Works (34)
Updated: April 3rd, 2024 22:59
2024 journal article
Iteration Complexity and Finite-Time Efficiency of Adaptive Sampling Trust-Region Methods for Stochastic Derivative-Free Optimization
IISE Transactions.
TL;DR:
It is proved that the adaptive sampling with interpolation-based trust regions or ASTRO-DF has a canonical iteration complexity of $\mathcal{O}(\epsilon^{-2})$ almost surely, which is the first guarantee of its kind without placing assumptions on the quality of function estimates or model quality or independence between them.
(via Semantic Scholar)
arxiv.org (repository)
Source: ORCID
Added: April 1, 2024
2023 article
Diagnostic Tools for Evaluating and Comparing Simulation- Optimization Algorithms
Eckman, D. J., Henderson, S. G., & Shashaani, S. (2023, January 5). INFORMS JOURNAL ON COMPUTING, Vol. 1.
author keywords: analysis of algorithms; simulation; design of experiments; efficiency
TL;DR:
This work develops performance measures and plots, and estimators thereof, to evaluate and compare solvers and diagnose their strengths and weaknesses on a testbed of simulation-optimization problems and provides supporting convergence theory.
(via Semantic Scholar)
Sources: ORCID, Web Of Science
Added: January 6, 2023
2023 webpage
Iteration Complexity and Finite-Time Efficiency of Adaptive Sampling Trust-Region Methods for Stochastic Derivative-Free Optimization
https://arxiv.org/abs/2305.10650
Source: ORCID
Added: July 15, 2023
2023 chapter
Monte Carlo Based Machine Learning
In Lecture Notes in Operations Research.
Source: ORCID
Added: November 18, 2023
2023 webpage
On Common-Random-Numbers and the Complexity of Adaptive Sampling Trust-Region Methods
(2023, August 4). https://optimization-online.org website: https://optimization-online.org/wp-content/uploads/2023/08/astrodf-complexity-online-version.pdf
Source: ORCID
Added: August 13, 2023
2023 article
Predicting additive manufacturing defects with robust feature selection for imbalanced data
Houser, E., Shashaani, S., Harrysson, O., & Jeon, Y. (2023, May 13). IISE TRANSACTIONS, Vol. 5.
author keywords: Smart manufacturing; feature extraction; simulation optimization; robust prediction; data uncertainty
Sources: ORCID, Web Of Science
Added: June 25, 2023
2023 article
Risk Score Models for Unplanned Urinary Tract Infection Hospitalization
Alizadeh, N., Vahdat, K., Shashaani, S., Swann, J. L., & Ozaltin, O. (2023, August 9).
TL;DR:
This work utilizes a sample of patients from the insurance claims data provided by the Centers for Medicare and Medicaid Services to develop and validate two risk score models for unplanned UTI hospitalization and provides a quantitative assessment of the significance of various risk factors.
(via Semantic Scholar)
Source: ORCID
Added: August 11, 2023
2023 article
SimOpt: A Testbed for Simulation-Optimization Experiments
Eckman, D. J., Henderson, S. G., & Shashaani, S. (2023, March 9). INFORMS JOURNAL ON COMPUTING, Vol. 3.
author keywords: simulation optimization; solvers; experimental design; common random numbers
TL;DR:
A major redesign of SimOpt is introduced, a testbed of simulation-optimization (SO) problems and solvers that ports the code to an object-oriented architecture in Python and provides a graphical user interface.
(via Semantic Scholar)
Sources: ORCID, Web Of Science
Added: March 10, 2023
2023 journal article
Statistical Inference on Simulation Output: Batching as an Inferential Device
Source: ORCID
Added: November 18, 2023
2023 journal article
Wake effect parameter calibration with large-scale field operational data using stochastic optimization
APPLIED ENERGY, 347.
author keywords: Offshore wind energy; Calibration; Wake model
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(Web of Science; OpenAlex)
Sources: ORCID, Web Of Science
Added: June 29, 2023
2022 article
Improved feature selection with simulation optimization
Shashaani, S., & Vahdat, K. (2022, May 30). OPTIMIZATION AND ENGINEERING, Vol. 5.
author keywords: Stochastic error analysis; Adaptive sampling; Predictive accuracy; Data-driven dependence; Reliability
TL;DR:
This work develops adaptive sampling strategies for large enough datasets, where the number of training and test resamples vary for each solution, and develops adaptive sample sizes, which reach the same quality level of recommended feature subsets but significantly faster than the fixed sample size version.
(via Semantic Scholar)
Sources: ORCID, Web Of Science
Added: June 4, 2022
2022 chapter
Personalized Predictions for Unplanned Urinary Tract Infection Hospitalizations with Hierarchical Clustering
In Springer Proceedings in Business and Economics (pp. 453–465).
TL;DR:
A hierarchical clustering approach that leverages existing knowledge and data-driven algorithms to partition the population into groups of similar risk, followed by building a LASSO-Logistic Regression model for each group, achieves more accurate and precise predictions and offers more granular feature importance insights for each patient group.
(via Semantic Scholar)
Source: ORCID
Added: January 29, 2021
2022 article
ROBUST SIMULATION OPTIMIZATION WITH STRATIFICATION
2022 WINTER SIMULATION CONFERENCE (WSC), pp. 2246–2257.
TL;DR:
This study shows that an adaptive sampling class of simulation optimization solvers called ASTRO-DF could become more robust with stratification, S-ASTRO-DF, and finds that while stratified sampling improves the algorithm's performance, its robustness is sensitive to the stratification structure.
(via Semantic Scholar)
Sources: ORCID, Web Of Science
Added: April 8, 2023
2021 conference paper
Improved Complexity Of Trust-Region Optimization For Zeroth-Order Stochastic Oracles with Adaptive Sampling
2021 Winter Simulation Conference (WSC).
Contributors: Y. Ha n & Q. Tran-Dinh *
TL;DR:
This paper reports in the numerical experience the finite-time superiority of the enhanced ASTRO-DF over state-of-the-art using the SimOpt library and gives several theoretical results, including iteration complexity, and renders almost sure convergence guarantees.
(via Semantic Scholar)
Source: ORCID
Added: March 30, 2022
2021 conference paper
Non-Parametric Uncertainty Bias and Variance Estimation via Nested Bootstrapping and Influence Functions
2021 Winter Simulation Conference (WSC).
Source: ORCID
Added: March 30, 2022
2021 conference paper
Parameter Calibration with Stratified Adaptive Stochastic Trust-region Optimization
INFORMS Workshop on Quality, Statistics, and Reliability.
Source: ORCID
Added: August 7, 2021
2021 conference paper
Wake Effect Calibration in Wind Power Systems with Adaptive Sampling Based Optimization
IISE Annual Conference Proceedings, 43–48. https://www.proquest.com/scholarly-journals/wake-effect-calibration-wind-power-systems-with/docview/2560890092
Source: ORCID
Added: August 7, 2021
2020 article
A SIMULATION OPTIMIZATION APPROACH FOR MANAGING PRODUCT TRANSITIONS IN MULTISTAGE PRODUCTION LINES
2020 WINTER SIMULATION CONFERENCE (WSC), pp. 1730–1741.
TL;DR:
This work uses simulation optimization to develop solutions and examine the impact of learning at a single machine on the rest of the system, laying the foundation for studying product transitions using realistic fab scale simulation models.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
12. Responsible Consumption and Production
(Web of Science)
Sources: ORCID, Web Of Science
Added: August 7, 2021
2020 article
SIMULATION OPTIMIZATION BASED FEATURE SELECTION, A STUDY ON DATA-DRIVEN OPTIMIZATION WITH INPUT UNCERTAINTY
2020 WINTER SIMULATION CONFERENCE (WSC), pp. 2149–2160.
TL;DR:
This work proposes a framework for simulation optimization over a high dimensional binary space in place of the classic greedy search in forward or backward selection or regularization methods, and provides insight for leveraging Monte Carlo methodology in probabilistic data-driven modeling and analysis.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: ORCID, Web Of Science
Added: August 7, 2021
2020 dataset
Simulation Optimization Library
https://github.com/simopt-admin/simopt
Source: ORCID
Added: July 15, 2023
2020 conference paper
Traffic Signal Control Simulation and Optimization
Winter Simulation Conference.
Source: ORCID
Added: January 29, 2021
2019 conference paper
ASTRO for Derivative-Based Stochastic Optimization: Algorithm Description & Numerical Experiments
2019 Winter Simulation Conference (WSC).
TL;DR:
ASTRO incorporates adaptively sampled function and gradient estimates within a trust-region framework to generate iterates that are guaranteed to converge almost surely to a first-order or a second-order critical point of the objective function.
(via Semantic Scholar)
Source: ORCID
Added: March 23, 2020
2019 journal article
Statistical Modeling in Absence of System Specific Data: Exploratory Empirical Analysis for Prediction of Water Main Breaks
JOURNAL OF INFRASTRUCTURE SYSTEMS, 25(2).
author keywords: Drinking water distribution systems; Replacement and rehabilitation planning; Asset management; Statistical modeling; Risk prioritization
UN Sustainable Development Goal Categories
6. Clean Water and Sanitation
(Web of Science)
Sources: Web Of Science, ORCID
Added: May 6, 2019
2018 journal article
ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Stochastic Optimization
SIAM Journal on Optimization.
author keywords: derivative-free optimization; simulation optimization; stochastic optimization; trust region
TL;DR:
The almost-sure convergence of ASTRO-DF's iterates to a first-order critical point when using linear or quadratic stochastic interpolation models is demonstrated.
(via Semantic Scholar)
Source: ORCID
Added: October 10, 2019
2018 journal article
Multi-Stage Prediction for Zero-Inflated Hurricane Induced Power Outages
IEEE Access, 6, 62432–62449.
author keywords: Power system analysis computing; data analysis; predictive models; risk analysis
TL;DR:
A new framework that operates in three stages by separating the prediction of whether or not power outages will occur from the number of customers without power is developed, and a weighted accuracy metric is introduced and investigated to investigate its benefits over mean absolute error.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(OpenAlex)
Source: ORCID
Added: October 10, 2019
2016 conference paper
ASTRO-DF: Adaptive sampling trust-region optimization algorithms, heuristics, and numerical experience
2016 Winter Simulation Conference (WSC).
TL;DR:
This paper describes and list ASTRO-DF, and discusses key heuristics that ensure good finite-time performance, including adaptive sampling and replication to keep the model error and the trust-region radius in lock-step, to ensure efficiency.
(via Semantic Scholar)
Source: ORCID
Added: October 10, 2019
2013 journal article
A Simulation Optimization Approach to Epidemic Forecasting
PLoS ONE.
MeSH headings : Algorithms; Computer Simulation; Epidemics; Florida / epidemiology; Forecasting; Humans; Influenza, Human / epidemiology; Models, Biological; Seasons; Virginia / epidemiology; Washington / epidemiology
TL;DR:
The SIMOP procedure combines an individual-based model and the Nelder-Mead simplex optimization method to forecast epidemics simulated over synthetic social networks representing Montgomery County in Virginia, Miami, Seattle and surrounding metropolitan regions.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(OpenAlex)
Source: ORCID
Added: October 10, 2019
2011 journal article
Single-machine batch scheduling minimizing weighted flow times and delivery costs
Applied Mathematical Modelling.
author keywords: Scheduling; Single machine; Batch delivery; Branch-and-bound; Weighted flow times
TL;DR:
This paper addresses scheduling a set of jobs on a single machine for delivery in batches to one customer or to another machine for further processing, considering the possibility of delivering jobs in batches and introducing batch delivery costs.
(via Semantic Scholar)
Source: ORCID
Added: October 10, 2019
Employment
Updated: November 16th, 2021 07:59
2019 - present
North Carolina State University Raleigh, NC, US
Assistant Prof. and Associate Faculty of Operations Research Graduate Program
Industrial and Systems Engineering
2016 - 2018
University of Michigan Ann Arbor, MI, US
Research Fellow
Industrial and Operations Engineering
Education
Updated: August 12th, 2023 08:13
2014 - 2016
Purdue University West Lafayette, IN, US
PhD
Industrial Engineering
2011 - 2014
Virginia Tech Blacksburg, VA, US
Master of Science
Systems Engineering and Operations Research
2009 - 2011
Purdue University West Lafayette, IN, US
Master of Science
Industrial Engineering
2004 - 2008
Southern Cross University Lismore, AU
Bachelor of Science
Applied Computing
2003 - 2008
Iran University of Science and Technology Tehran, IR
Bachelor of Science
Industrial Engineering
Funding History
Funding history based on the linked ORCID record. Updated: March 27th, 2024 10:16
grant
January 1, 2024 - December 1, 2025
Advancing the sustainability and resiliency of lagoon-sprayfield systems in Eastern North Carolina: Tool Development and Utilization
North Carolina Department of Transportation
grant
January 1, 2023 - December 31, 2025
Collaborative Research: Calibrating Digital Twins in the Era of Big Data with Stochastic Optimization
Directorate for Engineering
grant
July 1, 2022 - July 1, 2033
Adaptive Sampling Trust-region Methods for Nonconvex Stochastic Optimization
American Association of University Women
grant
January 1, 2022 - January 1, 2023
Impact of Future Climate Events on NC Animal Agriculture Systems
North Carolina State University
award
January 1, 2021 - January 1, 2022
Quantum Computing and Monte Carlo Methodology
North Carolina State University
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