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Which of the following statements about Evolutionary Solver are TRUE?
(Select all that apply)

A. Evolutionary Solver can evaluate complex objective functions better than Nonlinear Solver.

B. Nonlinear Solver is less likely than Evolutionary Solver to be unable to overcome discontinuities.

C. Evolutionary Solver is less likely than Nonlinear Solver to be unable to overcome discontinuities.

D. Nonlinear Solver can evaluate complex objective functions better than Evolutionary Solver.

E. Evolutionary Solver can evaluate complex objective functions better than Nonlinear Solver.

F. Evolutionary Solver is less likely than Nonlinear Solver to be unable to overcome discontinuities.

Answer :

The statements that are true include:

  • Evolutionary Solver can evaluate complex objective functions better than Nonlinear Solver
  • Evolutionary Solver is less likely than Nonlinear Solver to be unable to overcome discontinuities

What is the solver about?

As long as it is making a reasonable amount of progress, the Evolutionary Solver will keep looking for better solutions. If it cannot make enough progress within the time you have specified, it will stop and report the best solution found.

The Theory of Natural Selection, on which the evolutionary method is based, is effective in this situation because the ideal result has already been established. To put it simply, the solver begins with a random "population" of input value sets.The nonlinear analysis is converged using a nonlinear solver, such as NonlinearBlockGS or Newton. Every time there is a cyclic dependency between elements in your model, a nonlinear solver is required.

Learn more about discontinuity on:

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Rewritten by : Barada

The correct statements are:

  • Option 1 : Evolutionary Solver can evaluate complex objective functions better than Nonlinear Solver.
  • Option 2 : Nonlinear Solver is less likely than Evolutionary Solver to be unable to overcome discontinuities.

When determining which Solver to use in Excel, it's essential to consider the nature of the problem. The GRG Nonlinear engine is optimal for smooth nonlinear problems, while the Evolutionary engine is better suited for non-smooth problems.

Among the statements provided, the first and second statements are correct. Evolutionary Solver is indeed better at evaluating complex objective functions compared to Nonlinear Solver. Additionally, Nonlinear Solver is less likely than Evolutionary Solver to handle discontinuities efficiently.

  1. Evolutionary Solver can evaluate complex objective functions better than Nonlinear Solver.
  2. Nonlinear Solver is less likely than Evolutionary Solver to be unable to overcome discontinuities.

Therefore, the correct statements are:

  • Evolutionary Solver can evaluate complex objective functions better than Nonlinear Solver.
  • Nonlinear Solver is less likely than Evolutionary Solver to be unable to overcome discontinuities.