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The problems are solved using bilevel programming optimization methods.
The model equations are solved using an implicit finite difference method and a Newton Raphson algorithm53.
All matrix equations are solved using the Cholesky direct solver of the numerical library SuiteSparse44.
The production decisions are solved using some objective function and flux balance analysis.
Some examples are solved using the proposed iterative method.
Time dependent equations are solved using Newmark's time integration algorithm.
These aspects are solved using a multi-cellular genetic algorithm.
These BLMIs are solved using an iterative algorithm.
The governing equations are solved using finite volume methods.
The differential equations are solved using a power series approach.
Afterwards, these equations are solved using HPM method.
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