| Step 1. Initialize parameters. |
| (Population size); (Max number of generations); |
| Parameters of WDO: RT (RT coefficient); (The friction coefficient); (Maximum allowed speed); (Gravitational |
| constant); (Constant in the update equation). |
| Parameters of DE: (Mutation scale factor); (Crossover probability). |
| Step 2. Initialization populations. |
| Step 2.1. Generate one initial population with air particles, each air particle assign random location and velocity |
| , evaluation the population and identify the best solution of WDO algorithm ; |
| Step 2.2. Generate one initial population with individuals, evaluation the population and identify the best |
| solution . |
| Step 3. Identify the best solution among all particles in WDO and DE. |
| Step 4. While stopping criterion is not satisfied |
| Step 4.1. Running process of the WDO algorithm |
| for to the do |
| |
| Generate the trial velocity according to (8) |
| Generate the trial location by (9) |
| Evaluate the trial location |
| If |
| , |
| If |
| , |
| End if |
| End if |
| End for |
| Step 4.2. Running process of the DE algorithm |
| for to the do |
| |
| Generate using (11) |
| Generate the trial vector by (15) |
| Evaluate the trial vector |
| If |
| , |
| If |
| , |
| End if |
| End if |
| End for |
| Step 4.3. Identify the best solution |
| If |
| |
| Else |
| |
| End if |
| Step 4.4. Increment the generation count |
| Step 5. End while |
