For problems with smooth coefficients on smooth grids, the method is comparable with other second-order methods.
With mass lumping techniques and node-to-node matching grids, the method is fully explicit without solving any linear system.
Besides the target voxel grid, the interpolation method directly influences the deviation of SUVmax, MTV, and TLG.
When compared against standard locally-adaptive sparse grid methods, the present method uses many fewer number of collocation samples and is more accurate.
Only after heavy grid refinement the methods switch to converge to the true solution.
The location and movement of cells are defined in a Cartesian grid, however the methods are portable to other geometries.
States space Using the grid method, the state space is therefore a set of grids; each grid cell has an associated value stating, obstacle, free or goal state.
Therefore, the realization of the grid method for the solution of problem (3 -(4) is connected with some difficulties.
In this paper we suggest a scheme of the realization of the grid method for the solution of problem (3 -(4).
Four iterative methods are designed including the single grid method; the full single grid method; the V-cycle multigrid method and the FMG method.
