ChooseOptimizer

This module is a tool to select different optimization engines when using JuMP and to change solver options.

New in version 0.3: Default solver is HiGHS and set_solver defaults to non-verbose output.

The set_solver function is used to select the optimization package desired. Without any arguments it selects the HiGHS optimizer. Otherwise, set_solver(NAME) is used to choose the desired optimizer, e.g., set_solver(Gurobi). (For this to work, this must follow using Gurboi.)

The function get_solver is a replacement for JuMP's with_solver function.

Instead of this:

MOD = Model(with_solver(HiGHS.Optimizer))

we do this:

set_solver(HiGHS)
MOD = Model(get_solver())

The default solver is HiGHS.

The supported solvers are:

• Cbc
• CPLEX
• GLPK
• Gurobi
• HiGHS

Solver options can be set up using these functions:

• set_solver_options(kwd, val) adds the option whose name is given by the symbol kwd to be the value val. To add several options, use this several times.
• set_solver_options(d::Dict) adds all the key/value entries in d as options by repeated calls to set_solver_options(key,value).
• clear_solver_options() erases all solver options.
• get_solver_options() returns a dictionary of the options that are currently set.

When a JuMP model is created using Model(get_solver()) the options are passed along.

Note that each call to set_solver clears all options and then resets the output (verbose) level.

The function set_solver takes an optional second Boolean argument to set the output level:

set_solver(OPT_NAME::Module = HiGHS, verbose::Bool = false)

The set_solver_verbose() function can be used to tell the solver to be verbose in its operation. Alternatively, set_solver_verbose(false) suppresses output.

The action of set_solver_verbose is through set_solver_options.

At present, this function only knows how to do this for the Cbc, CPLEX, GLPK, Gurobi, and HiGHS optimizers. It is easy, however, to add additional solvers by modifying the file set_verbose.jl or in the REPL with a command that looks like this:

ChooseOptimizer._solver_table["NAME"] = ("opt_name", yes_val, no_val)

where

• NAME is the name of the solver,
• opt_name is the option name that controls output for that solver,
• yes_val is the value for verbose output, and
• no_val is the value for supressing output.