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Variables reduction strategies are presented to accelerate solving the model.
We apply two ranking functions for solving the model.
By solving the model, the results illustrate the significant reduction in transportation costs.
A general-purpose numerical solver is used for solving the model and plotting the pertinent results.
By solving the model for various values of ε, the approximated Pareto frontier is constructed.
Then, an algorithm designed by Genetic Algorithm (GA) is used for solving the model.
The transient temperature field is obtained by solving the model through Laplace and inverse-Laplace transformation.
A numerical method for solving the model Boltzmann equation using arbitrary order polynomials is presented.
Primary RA responsibilities (or rather learning opportunities!) include empirical work using the US Census data and computational work in analyzing and solving the model.
As a bilevel problem with an NP-hard lower level problem, there is no algorithm for solving the model exactly.
The convergence reliability in successfully solving the model for a wide-range of operation conditions was subsequently investigated.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com