
optimize(+Objective, -Cost)

   Optimise Objective (minimise or maximise) with the external solver.

Arguments
   Objective           Objective function: min(CostExpr) or max(CostExpr)
   Cost                Value of the optimal solution

Type
   library(eplex)

Description

    Objective is either min(Expr) or max(Expr) where Expr is a linear
    expression (or quadratic if supported by the external solver).
    This calls the external solver's optimizer and succeeds if
    it finds an optimum.  In this case the problem variables get
    instantiated to the solution values, and Cost gets bound to the cost of
    this solution.  Note that this will find at most one solution, ie. you
    won't get alternative optima on backtracking.


    This primitive allows the external solver to be used as a black box:
    ECLiPSe is used as a modeling language and the external solver does all
    the solving. Linear constraints are first set up, and then this primitive
    is called to invoke the external solver on these constraints.



Fail Conditions
   The solver did not find a solution for Objective.


