This work introduces novel operator splitting alternating direction implicit (ADI) schemes to overcome numerical difficulties in solving pseudo-time coupled nonlinear partial differential equations (PDEs) for biomolecular solvation analysis.
In addition, to overcome the difficulties in solving the objectives of all the scenarios, scenario bundling and sensitivity analysis algorithms are developed to improve the computational efficiency.
A variational formulation equivalent to these equations transformed into a recursive quadratic programming problem by finite element method is used to overcome the difficulties in solving simultaneously the nonlinear governing equations and geometric contact condition.
To overcome the difficulties in solving the plate-foundation equilibrium equations, a variational formulation equivalent to these equations is presented from which three alternative linear complementary problems are derived and solved by Lemke's complementary pivoting algorithm to obtain no-contact regions where the plate lifts up away from the foundation and the subgrade reaction.
To overcome these numerical oscillations in solving the transient advection diffusion equations involved in the heat transfer and solute transport processes, we employ a stabilized finite element approach, the subgrid scale/gradient subgrid scale method (SGS/GSGS).
A genetic algorithm, modified to overcome some specific pitfalls in solving ordinary differential equations, is then used to search for the global optimum that minimizes the objective function within parameter ranges.
This study discusses a method that overcomes the size limitations in solving large size multilevel hierarchical hub location problem with a single allocation by using a stepwise solving approach called CM-GATS.
The technique not only reduces the number of terms involved in each iteration but also overcomes the difficulty faced in solving complicated integrals.
Problems related to the analysis of mixed cultures, presently not yet fully solved, are likely to be overcome in the near future, and attempts to identify pathogens directly in the clinical samples have already yielded promising results [14].
In order to overcome these drawbacks, solving the linear system of equations inexactly and the non-monotone line search technique are used in our smoothing-type method.
