eldo_user

Figure 13-2. Discretization of Design Variables
Optimization
Discretized Design Variables
The continuous box represents the feasible domain specified by the upper and lower bounds,
and the black bullets are the feasible points where the final parameters are allowed to lie.
The Eldo optimizer initially ignores discretization requirements, solving the optimization
problem with real variables. All the design variables are then rounded to the nearest point onto
the grid at the end of optimization.
Note
This strategy is not guaranteed to give solutions that are close to optimal. See “Solving
Problems with Pseudodiscrete Variables” on page 668 for a detailed example.
When the lower bound is a finite number, the set of discretized points are as follows:
{x l (i) , x l (i) + δ i , x l (i) + 2δ i , …}
Where δ i > 0 is the given increment.
When the lower bound is infinite (x l (i) = ∞), the grid is started from the upper bound, if it is
finite. The set of discretized points is then:
{x u (i) , x u (i) + δ i , x u (i) + 2δ i , …}
When a design variable is unbounded (x l (i) = −∞ and x u (i) = ∞), discretization is not considered.
Related Topics
Optimization in Eldo
Design Objectives
Optimization Methods
Conducting an Eldo Optimization
Eldo® User's Manual, 15.3 595