| Definition: |
| : the population size; |
| : the maximum number of generations for stopping criterion; |
| : dimension of the problem; |
| : the decision matrix with the size of ; |
| : the function value vector with the size of 1; |
| : the learning rate for conventional mutation strategy. |
(1) | BEGIN |
(2) | Set mutation probability and learning rate ; |
(3) | Create a randomly initialized population {}; |
(4) | Let ; |
(5) | while do |
(6) | while do |
(7) | Locate in X and obtain its nearest superior neighbors and inferior neighbors , with ; |
(8) | Select as the tournament best from () and as the tournament worst from (), with ; |
(9) | Select as the ; |
(10) | Generate three random values , , and , where , , and ; |
(11) | Compute the convex combination vector weights , , and , according to ; |
(12) | Obtain the combination vector: ; |
(13) | Generate the random values , , and , where , , and again; |
(14) | Compute the learning rates , , and , according to ; |
(15) | ifthen |
(16) | The triangular mutation vector ; |
(17) | else |
(18) | The conventional mutation vector ; |
(19) | end if |
(20) | Repair if it violates the upperbound or lowerbound; |
(21) | Generate ; |
(22) | whiledo |
(23) | if or then |
(24) | ; |
(25) | else |
(26) | ; |
(27) | end if |
(28) | end while |
(29) | if then |
(30) | ; |
(31) | if then |
(32) | ; |
(33) | end if |
(34) | else |
(35) | ; |
(36) | end if |
(37) | end while |
(38) | end while |
(39) | Return; |
(40) | END |