| Begin |
| (1) Initial the parameter values of the algorithm, generate the random initial vector values and set the iteration number . |
| (2) Evaluate fitness values of each individual and determine the current best individual with the best objective value. |
| Check whether the stopping criterion is met. If the stopping criterion is met, then output the best solution; |
| otherwise update the iteration number and continue the iteration process until the stopping criterion is met. |
| (3) Keep the best solution of the last iteration, and get a set of new solutions by |
| Lévy flight, the Lévy flight is performed according to (4). |
| (4) Evaluate the fitness value of the new solution , and compare with which represents the solution of |
| the th iteration. If is better than , then replace by , otherwise, not abandoning the solution |
| at once but accepting the solution with probability , where is the change in the fitness value |
| . is Boltzmann’s constant. is the current temperature. Select a random variable , , |
| if , then accept the new solution and use the solution as the starting point for the next iteration. Otherwise, |
| abandon the solution, then a set of solution are obtained. |
| (5) A fraction () of worse nests are abandoned and new ones are built. |
| (6) Implement the orthogonal design strategy procedures. |
| (7) Go to step (2) |
| End |
