Morphing Wing Structural Optimization Using Opposite-Based Population-Based Incremental Learning and Multigrid Ground Elements

Algorithm 2

MPBIL computational steps.

Initialization probability matrix , external Pareto archive Pareto = .

(1) Generate a binary population from (see Figure 8).

(2) Decode the binary population to be and find the objective values .

(3) Update Pareto by replacing it with the non-dominated solutions of a union set Pareto    .

(4) If the number of members in Pareto exceeds the predefined archive size , remove some of them by using an archiving

  technique.

(5) If the termination criterion is fulfilled, stop the procedure. Otherwise, go to step 6:

(6) Update .

(6.1) For = 1 to .

   (6.1.1) Select binary solutions from Pareto randomly.

   (6.1.2) Generate using (4).

   (6.1.3) Update the th row of by using (3).

   (6.1.4) Generate rand a uniform random number.

   (6.1.5) If rand < the predefined mutation probability, update the th row of using (5).

(6.2) Next .

(7) Go to step 1.