OptSolution

OptSolution(opt, decision)

Returns the solution to an optimization problem «opt» specified by DefineOptimization.

If you specify as «decision» the name of a global Decision variable used in the Optimization, it returns the solution (optimal value) for that decision. If you omit «decision», it returns the solution to all Decision variables as a vector indexed by a local index .Vars, which contains all the decision values flattened so that each solution is a scalar.

Evaluating a variable that uses OptSolution() will trigger an attempt to solve the optimization problem, unless it has already been solved by another call to OptSolution, or a related function, such as OptStatusText.

OptSolution returns a result when it finds an optimal, or likely optimal solution. If it finds no feasible solution it gives a warning if you have Show Result Warnings turned on. It is entirely possible that there is no solution, or that the solver could not find a feasible solution, in which cases the values returned by OptSolution are arbitrary. So, you should always check OptStatusText or OptStatusNum to check that it has found a feasible and optimal solution.

If the Optimization used a local variable, say D1, as a Decision, declared as local in the expression using DefineOptimization, for example

Variable OptimizeIt := VAR d1 := 0; DefineOptimization(Decisions: d1; ....)

you can get its solution by defining a local with the same identifier, D1, preceding OptSolution(), and giving D1 as «decision»:

Variable D1_solution := VAR d1 := 0; OptSolution(OptimizeIt, d1)

Example

Find the minimum of the GammaFn(x) for x > 0:

Var x := 1;

Var opt := DefineOptimization(decisions: x, minimize: GammaFn(x), domain: Continuous(lb: 0));

OptSolution(opt, x)

History

This function was introduced in Analytica 4.3, in earlier versions, use LpSolution.

See Also

• Using SetContext to efficiently solve NLPs
• DefineOptimization
• OptInfo
• OptStatusText
• OptStatusNum
• OptStatusText
• OptStatusNum
• OptObjective