Linear Versus Nonlinear Models
If you have a linear problem, make sure that
you've checked the Assume Linear Model box in the Solver Options
dialog. If you haven't checked this box, the Solver assumes that
the problem is nonlinear. The Solver is many times faster on
linear than on nonlinear problems, and this speed difference rises
very rapidly with an increased number of decision variables.
When the problem is linear, the Solver will
recalculate the model approximately N times, where N is the number
of decision variables (or changing cells). This happens once, during
the phase when "Setting Up Problem..." appears on the
Excel message bar. When the problem is nonlinear, the Solver must
recalculate the model N times on every major iteration, in order to
update its estimate of how the objective function and constraints
are changing. For this reason, you'll see the Solver spending much
more time on each Trial Solution reported on the Excel
message bar for a nonlinear problem. Further, on linear problems the
Solver is able use faster and more reliable methods to choose the
decision variable values for the next trial solution.
We often see Solver models from users who are
convinced that their problems are intrinsically nonlinear, yet we
find that with a modest effort (sometimes no effort) these models
can be set up as linear problems. If solution time is an issue, it
is worth your while to consider whether the model really could be
formulated as a linear problem. For more information on this topic,
consult our Solver Tutorial, or ask for access to our protected
Support pages discussing piecewise linear approximations for
nonlinear functions.
Next: Eliminating Non-Essential Calculations
Back to Improving Slow Solution Times
Back to Standard Excel Solver
Support Information
