Dividend Optimization Professors in Global

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Albert Berahas
University of Michigan United States of America
distributed optimization
machine learning optimization
stochastic optimization
derivative-free optimization
constrained optimization
nonlinear optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
distributed optimization
optimization algorithms
stochastic optimization
constrained optimization
nonlinear optimization
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Marina Epelman
University of Michigan United States of America
mathematical optimization
discrete optimization
integer optimization
optimization under uncertainty
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Cynthia Vinzant
University of Washington United States of America
mathematical optimization
discrete optimization
linear optimization
combinatorial optimization
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Eric Kerrigan
Imperial College London United Kingdom
dynamic optimization
numerical optimization methods
control optimization
multi-objective optimization
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Mahdi Mehrtash
Johns Hopkins University United States of America
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distributed optimization
global optimization
stochastic optimization
power system optimization
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Shixuan Zhang
Texas A&M University United States of America
integer optimization
robust optimization
stochastic optimization
polynomial optimization
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John Chinneck
Carleton University Canada
optimization
feasibility optimization
mixed integer optimization
nonlinear optimization
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Katya Scheinberg
Georgia Institute of Technology United States of America
optimization
continuous optimization
derivative-free optimization
convex optimization
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Dick Den Hertog
University of Amsterdam Netherlands
linear optimization
optimization in machine learning
robust optimization
nonlinear optimization
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Ignacio Grossmann
Carnegie Mellon University United States of America
discrete optimization
supply chain optimization
continuous optimization
energy systems optimization
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Ruth Misener
Imperial College London United Kingdom
optimization models
robust optimization
data-driven optimization
computational optimization
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Kalyanmoy Deb
Michigan State University United States of America
process optimization
hybrid optimization algorithms
computational optimization
multi-objective optimization
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Michael Patriksson
University of Gothenburg Sweden
mathematical optimization
convex optimization
combinatorial optimization
nonlinear optimization
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Merve Bodur
University of Edinburgh United Kingdom
robust optimization
inverse optimization
multiobjective optimization
combinatorial optimization
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Merve Bodur
University of Edinburgh United Kingdom
robust optimization
inverse optimization
multiobjective optimization
combinatorial optimization
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Michael Patriksson
Chalmers University of Technology Sweden
non-differentiable optimization
convex optimization
combinatorial optimization
nonlinear optimization
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Siva Maguluri
Georgia Institute of Technology United States of America
optimization
distributed optimization
stochastic optimization
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John Jørgensen
Technical University of Denmark Denmark
dynamic optimization
numerical optimization
process optimization
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Yashar Pourrahimian
University of Alberta Canada
optimization
mining optimization
data-driven optimization
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Mark Daskin
University of Michigan United States of America
mathematical optimization
discrete optimization
integer optimization
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