The Excel spreadsheet package comes with solvers for linear, nonlinear, and integer programming; it accepts enhanced add-in solvers as well. Their principal advantage lies in allowing all aspects of optimization — including formulation, solution, and analysis of results — to be performed within the spreadsheet environment. In particular, variables and constraints can be defined directly in terms of ranges of spreadsheet cells.
AMPL incorporates a far richer language than spreadsheet optimizers for describing optimization problems. As a result, AMPL is much more natural and reliable for developing and maintaining complex models. The difference is particularly pronounced when many model components have more than two dimensions (or more than two subscripts or indices, in AMPL terms).
By avoiding much of the spreadsheet overhead, AMPL also generates model instances faster than spreadsheet optimizers. AMPL’s speed advantage is significant for a few thousand model components, and becomes relatively greater as problem size increases.
AMPL’s interface design encourages developers to hook additional solvers to AMPL. Thus AMPL is available with a greater variety of solvers than spreadsheet optimizers.
AMPL models can read and write spreadsheet data that is structured in the form of relational tables, through use of the
read table and
write table commands.