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These aspects are solved using a multi-cellular genetic algorithm.
The differential equations are solved using a power series approach.
The governing equations are solved using a finite-volume approach.
The resulting discretized equations are solved using a multigrid method.
Runtime BVPs are solved using a collection of Capacitance Matrix Algorithms (CMAs) based on the Sherman-Morrison-Woodbury formula.
The governing equations, a two-point boundary problem, are solved using a relaxation method.
The MILP problems are solved using a branch and bound method.
The governing equations are solved using a minimising Newton Raphson technique.
We propose models that are solved using a commercial software, that address this problem.
The governing equations are solved using a modified MAC (Marker and Cell) method.
The diffusive components are solved using a standard Galerkin finite element method.
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