Zelda Zabinsky | University of Washington (original) (raw)

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Papers by Zelda Zabinsky

Research paper thumbnail of Prevention of seasonal influenza outbreak via healthcare insurance

IISE transactions on healthcare systems engineering, Nov 25, 2022

Research paper thumbnail of Simulation-driven task prioritization using a restless bandit model for active sonar missions

Winter Simulation Conference, Dec 6, 2015

Research paper thumbnail of Storage Synthesis of Power Systems via Dynamic Meta-control Schema

TechConnect Briefs, Oct 18, 2021

Research paper thumbnail of Designing and analyzing healthcare insurance policies to reduce cost and prevent the spread of seasonal influenza

Research paper thumbnail of Analysis and development of random search algorithms

This dissertation research addresses several issues in global optimization by developing complexi... more This dissertation research addresses several issues in global optimization by developing complexity analysis for random search algorithms, by constructing new algorithms and by applying existing algorithms in engineering design. Markov chain theory is used to develop models that can be used to analyze random search algorithms. Complexity analysis is set forth for several random search algorithms, including a combination of Pure Adaptive Search (PAS) and Pure Random Search (PRS) in a single algorithm. A probability of accepting non-improving points as is typically done in Simulated Annealing type algorithms is added to the analysis. An exact expression for an upper bound for the expected number of iterations to convergence is derived, and for special cases an exact expression is derived for the expected number of iterations to find the optimum. Numerical results are obtained for an algorithm called Hesitant Adaptive Search (HAS), by performing simulations for the algorithm. The results are compared with theoretical predictions. The Improving Hit-and-Run algorithm is also modeled and analyzed using Markov chains. A new algorithm, called the Hybrid Algorithm, is set forth and tested on several global optimization test problems. The hybrid algorithm is motivated by the complexity results that were derived for the random search algorithms. The algorithm combines interval methods and random search methods in a single algorithm. Finally the random search algorithm, Improving Hit-and-Run, is applied in engineering design to optimally design composite aircraft fuselage structures.

Research paper thumbnail of A Multi-Fidelity Rollout Algorithm for Dynamic Resource Allocation in Population Disease Management

Health Care Management Science, Sep 7, 2018

Research paper thumbnail of A branch and bound algorithm for dynamic resource allocation in population disease management

Operations Research Letters, Nov 1, 2019

Research paper thumbnail of Prefabrication supply chains with multiple shops: Optimization for job allocation

Automation in Construction, Apr 1, 2022

Research paper thumbnail of Optimization of composite I-sections using fiber angles as design variables

Composite Structures, Aug 1, 2001

Research paper thumbnail of Stochastic optimization with adaptive restart: a framework for integrated local and global learning

Journal of Global Optimization, Jul 28, 2020

Research paper thumbnail of COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

Medical Decision Making, Mar 18, 2021

Research paper thumbnail of Optimizing the Geometry of Wildlife Corridors in Conservation Reserve Design

Operations Research, Nov 1, 2018

Research paper thumbnail of Impact of Vaccination and Non-Pharmaceutical Interventions with Possible COVID-19 Viral Evolutions Using an Agent-Based Simulation

Research paper thumbnail of Message Scheduling Optimization with Energy Constraints and Uncertain Demands in a Store-and-Forward Nanosatellite Communications Architecture

Research paper thumbnail of Dynamic Message Scheduling with Uncertain Demands in a Store-and-Forward Nanosatellite Communications Architecture

Research paper thumbnail of COVID-19 Pandemic Response Simulation: Impact of Non-pharmaceutical Interventions on Ending Lockdowns

medRxiv (Cold Spring Harbor Laboratory), May 4, 2020

Research paper thumbnail of Optimal collection of medical specimens and delivery to central laboratory

Annals of Operations Research, 2019

We propose an efficient algorithm to provide transportation routes and schedules to pick up medic... more We propose an efficient algorithm to provide transportation routes and schedules to pick up medical specimens from clinics, physician’s offices, and hospitals and deliver them to a central laboratory quickly. This healthcare vehicle routing and scheduling problem differs from existing vehicle routing problems primarily in that, instead of minimizing driving time, the objective is to minimize the completion time, that is, the time from when the specimen is available for pickup until it is delivered to the central laboratory. We combine the routing problem with scheduling of vehicles and formulate a mixed integer linear program. We present a new algorithm to solve this optimization problem, called the Vehicle Routing and Scheduling Algorithm (VeRSA). VeRSA uses an indexing method inspired by scheduling methods to efficiently traverse a branch-and-bound tree associated with the mixed integer program. Instead of using a linear programming relaxation, as is common, we prove several propositions that lead to expressions that are fast to compute. We also prove a theoretical lower bound to provide some information on an optimality gap. Numerical results on three small and three large test problems demonstrate the high quality of solutions provided by VeRSA. The data in the large test problems are based on data provided by the University of Washington Medical Center (with modifications to protect confidentiality). The computational speed of VeRSA makes it applicable to real-time operational decisions when demand may be updated at any time due to cancellations or additional pickups. This model is applicable to other types of pickup and delivery systems where the waiting time of a package is important, such as perishable items.

Research paper thumbnail of Using a game-theoretic approach to design optimal health insurance for chronic disease

IISE Transactions on Healthcare Systems Engineering, 2019

Research paper thumbnail of Simulation-driven task prioritization using a restless bandit model for active sonar missions

2015 Winter Simulation Conference (WSC), 2015

Research paper thumbnail of COVID-19 Endemic Plan: Impact of Vaccination and Non-pharmaceutical Interventions with Viral Variants and Waning Immunity Using an Agent-Based Simulation

BackgroundsDespite the widespread distribution of SARS-CoV-2 vaccines, the COVID-19 pandemic cont... more BackgroundsDespite the widespread distribution of SARS-CoV-2 vaccines, the COVID-19 pandemic continues with highly contagious variants and waning immunity. Low disease severity of the Omicron variant gives society hope that the COVID-19 pandemic could end.MethodsWe develop an agent-based simulation to explore the impact of COVID-19 vaccine willingness, booster vaccination schedule, vaccine effectiveness, and non-pharmaceutical interventions (NPIs) on reducing COVID-19 deaths while considering immunity duration and disease severity against the Omicron variant. The model is calibrated to the greater Seattle in year 2020 by observing local epidemic data. The simulation is run to the end of year 2024 to observe long-term effects.ResultsResults show that an NPI policy that maintains low levels of NPIs can reduce mortality by 35.1% compared to fully opening the society. A threshold NPI policy is especially helpful when the disease severity of the Omicron variant is high, or booster vaccin...

Research paper thumbnail of Prevention of seasonal influenza outbreak via healthcare insurance

IISE transactions on healthcare systems engineering, Nov 25, 2022

Research paper thumbnail of Simulation-driven task prioritization using a restless bandit model for active sonar missions

Winter Simulation Conference, Dec 6, 2015

Research paper thumbnail of Storage Synthesis of Power Systems via Dynamic Meta-control Schema

TechConnect Briefs, Oct 18, 2021

Research paper thumbnail of Designing and analyzing healthcare insurance policies to reduce cost and prevent the spread of seasonal influenza

Research paper thumbnail of Analysis and development of random search algorithms

This dissertation research addresses several issues in global optimization by developing complexi... more This dissertation research addresses several issues in global optimization by developing complexity analysis for random search algorithms, by constructing new algorithms and by applying existing algorithms in engineering design. Markov chain theory is used to develop models that can be used to analyze random search algorithms. Complexity analysis is set forth for several random search algorithms, including a combination of Pure Adaptive Search (PAS) and Pure Random Search (PRS) in a single algorithm. A probability of accepting non-improving points as is typically done in Simulated Annealing type algorithms is added to the analysis. An exact expression for an upper bound for the expected number of iterations to convergence is derived, and for special cases an exact expression is derived for the expected number of iterations to find the optimum. Numerical results are obtained for an algorithm called Hesitant Adaptive Search (HAS), by performing simulations for the algorithm. The results are compared with theoretical predictions. The Improving Hit-and-Run algorithm is also modeled and analyzed using Markov chains. A new algorithm, called the Hybrid Algorithm, is set forth and tested on several global optimization test problems. The hybrid algorithm is motivated by the complexity results that were derived for the random search algorithms. The algorithm combines interval methods and random search methods in a single algorithm. Finally the random search algorithm, Improving Hit-and-Run, is applied in engineering design to optimally design composite aircraft fuselage structures.

Research paper thumbnail of A Multi-Fidelity Rollout Algorithm for Dynamic Resource Allocation in Population Disease Management

Health Care Management Science, Sep 7, 2018

Research paper thumbnail of A branch and bound algorithm for dynamic resource allocation in population disease management

Operations Research Letters, Nov 1, 2019

Research paper thumbnail of Prefabrication supply chains with multiple shops: Optimization for job allocation

Automation in Construction, Apr 1, 2022

Research paper thumbnail of Optimization of composite I-sections using fiber angles as design variables

Composite Structures, Aug 1, 2001

Research paper thumbnail of Stochastic optimization with adaptive restart: a framework for integrated local and global learning

Journal of Global Optimization, Jul 28, 2020

Research paper thumbnail of COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

Medical Decision Making, Mar 18, 2021

Research paper thumbnail of Optimizing the Geometry of Wildlife Corridors in Conservation Reserve Design

Operations Research, Nov 1, 2018

Research paper thumbnail of Impact of Vaccination and Non-Pharmaceutical Interventions with Possible COVID-19 Viral Evolutions Using an Agent-Based Simulation

Research paper thumbnail of Message Scheduling Optimization with Energy Constraints and Uncertain Demands in a Store-and-Forward Nanosatellite Communications Architecture

Research paper thumbnail of Dynamic Message Scheduling with Uncertain Demands in a Store-and-Forward Nanosatellite Communications Architecture

Research paper thumbnail of COVID-19 Pandemic Response Simulation: Impact of Non-pharmaceutical Interventions on Ending Lockdowns

medRxiv (Cold Spring Harbor Laboratory), May 4, 2020

Research paper thumbnail of Optimal collection of medical specimens and delivery to central laboratory

Annals of Operations Research, 2019

We propose an efficient algorithm to provide transportation routes and schedules to pick up medic... more We propose an efficient algorithm to provide transportation routes and schedules to pick up medical specimens from clinics, physician’s offices, and hospitals and deliver them to a central laboratory quickly. This healthcare vehicle routing and scheduling problem differs from existing vehicle routing problems primarily in that, instead of minimizing driving time, the objective is to minimize the completion time, that is, the time from when the specimen is available for pickup until it is delivered to the central laboratory. We combine the routing problem with scheduling of vehicles and formulate a mixed integer linear program. We present a new algorithm to solve this optimization problem, called the Vehicle Routing and Scheduling Algorithm (VeRSA). VeRSA uses an indexing method inspired by scheduling methods to efficiently traverse a branch-and-bound tree associated with the mixed integer program. Instead of using a linear programming relaxation, as is common, we prove several propositions that lead to expressions that are fast to compute. We also prove a theoretical lower bound to provide some information on an optimality gap. Numerical results on three small and three large test problems demonstrate the high quality of solutions provided by VeRSA. The data in the large test problems are based on data provided by the University of Washington Medical Center (with modifications to protect confidentiality). The computational speed of VeRSA makes it applicable to real-time operational decisions when demand may be updated at any time due to cancellations or additional pickups. This model is applicable to other types of pickup and delivery systems where the waiting time of a package is important, such as perishable items.

Research paper thumbnail of Using a game-theoretic approach to design optimal health insurance for chronic disease

IISE Transactions on Healthcare Systems Engineering, 2019

Research paper thumbnail of Simulation-driven task prioritization using a restless bandit model for active sonar missions

2015 Winter Simulation Conference (WSC), 2015

Research paper thumbnail of COVID-19 Endemic Plan: Impact of Vaccination and Non-pharmaceutical Interventions with Viral Variants and Waning Immunity Using an Agent-Based Simulation

BackgroundsDespite the widespread distribution of SARS-CoV-2 vaccines, the COVID-19 pandemic cont... more BackgroundsDespite the widespread distribution of SARS-CoV-2 vaccines, the COVID-19 pandemic continues with highly contagious variants and waning immunity. Low disease severity of the Omicron variant gives society hope that the COVID-19 pandemic could end.MethodsWe develop an agent-based simulation to explore the impact of COVID-19 vaccine willingness, booster vaccination schedule, vaccine effectiveness, and non-pharmaceutical interventions (NPIs) on reducing COVID-19 deaths while considering immunity duration and disease severity against the Omicron variant. The model is calibrated to the greater Seattle in year 2020 by observing local epidemic data. The simulation is run to the end of year 2024 to observe long-term effects.ResultsResults show that an NPI policy that maintains low levels of NPIs can reduce mortality by 35.1% compared to fully opening the society. A threshold NPI policy is especially helpful when the disease severity of the Omicron variant is high, or booster vaccin...

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