A5056796690- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Simulation Techniques and Applications
- Advanced Optimization Algorithms Research
- Probabilistic and Robust Engineering Design
- Composite Structure Analysis and Optimization
- Topology Optimization in Engineering
- Advanced Bandit Algorithms Research
- Optimization and Search Problems
- Vehicle Routing Optimization Methods
- Markov Chains and Monte Carlo Methods
- COVID-19 epidemiological studies
- Neural Networks and Applications
- Evolutionary Algorithms and Applications
- Numerical Methods and Algorithms
- Structural Analysis and Optimization
- Advanced Manufacturing and Logistics Optimization
- Facility Location and Emergency Management
- Scheduling and Optimization Algorithms
- Vaccine Coverage and Hesitancy
- Statistical Methods and Inference
- Manufacturing Process and Optimization
- Advanced Control Systems Optimization
- Optimization and Mathematical Programming
- Gaussian Processes and Bayesian Inference
University of Washington
2016-2025
Seattle University
1996-2023
Bellevue Hospital Center
2015
Dallas County
2013
Transmission enhancement in a competitive electricity market is analyzed terms of its impact on the social welfare. A formulation welfare and utility functions are derived this research. Variations supply demand during year considered transmission decisions. The proposed optimization problem solved to determine congestion status under optimal condition existing system. options compared quantitatively demonstrate their ability increase welfare, which provides valuable information for...
Micro-grids require active control to maintain quality of service and interface with the power grid in a bi-directional manner. Further, micro-grids must be justified by environmental, governmental, economic viability. We present programmable architecture for active, optimal distributed elements achieve desired behavior. A unique aspect this is include inductive engine learning local dynamics generators loads micro-grid. It generates feedback laws that are adapted current status micro-grid,...
Abstract This paper presents a model and an algorithm for scheduling system in which parts are processed through chemical processing tank line. The line is equipped with one piece of material-handling equipment. modelled mixed integer linear programming formulation. formulation then used to develop heuristic algorithm. generates the optimum or near schedule easy apply practice where no defectives permitted.
Reverse logistics play a significantly increased role in supply chains. Producers are incorporating reverse into their chain design because of governmental legislation, economic benefits from product recovery, and customers' demands for better environmental practices. Motivated producers face two main challenges network design: (1) how do you build recovery activities traditional forward networks? (2) manage the impact uncertainty chain? Moreover, need to consider many tradeoffs leading...
Hit-and-run, a class of MCMC samplers that converges to general multivariate distributions, is known be unique in its ability mix fast for uniform distributions over convex bodies. In particular, rate convergence distribution low order polynomial the dimension. However, when body interest difficult sample from, typically hyperrectangle introduced encloses original body, and one-dimensional acceptance/rejection performed. The mixing analysis hit-and-run does not account this sampling often...
Abstract Planning vaccine distribution in rural and urban poor communities is challenging, due part to inadequate vehicles, limited cold storage, road availability, weather conditions. The University of Washington VillageReach jointly developed tested a user‐friendly, Excel spreadsheet based optimization tool for routing scheduling efficiently distribute vaccines other medical commodities health centers across Mozambique. This paper describes the process used define problem obtain feedback...
As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving balance combinations of nonpharmaceutical interventions (NPIs) keep people safe and minimize social disruptions. We developed calibrated an agent-based simulation model COVID-19 outbreaks in greater Seattle area. The simulated NPIs, including distancing, face mask use, school closure, testing, contact tracing with variable compliance effectiveness identify optimal NPI that can control spread virus a...
Teams of first responders work together to effectively manage a community-wide crisis. Traditionally, key groups such as police, fire, and medical are each trained for specific emergency procedures. Emergency response teams design training exercises augment an individual's cognition associated with performing time critical roles. The aggregation all individual cognition, distributed through communications, suggests situation awareness that incident commander requires perform optimal...