Pseudo-code of quantum-based genetic algorithm
| At t = 0, Initialize Population |
| Decode P(t)Q in accordance with the problem |
| Calculate the fitness values of each individual solution in decoded population PQ(t) |
| Observe the best solution and store it |
| If the stopping criteria is satisfied, then go to step 9 |
| At t = t+1 update PQ(t) to PQ(t+1) by applying the quantum rotation |
| Again, decode PQ(t+1) in accordance with the problem |
| Calculate the fitness value of each individual; solution in decoded population PQ(t) |
| Observe the best solution and store it |
| Execute mutation operator |
| If satisfied, then solution obtained |
| If the stopping criterion is not satisfied, go to step 5 |
| At |
| Decode |
| Calculate the fitness values of each individual solution in decoded population PQ( |
| Observe the best solution and store it |
| If the stopping criteria is satisfied, then go to step 9 |
| At |
| Again, decode PQ( |
| Calculate the fitness value of each individual; solution in decoded population PQ( |
| Observe the best solution and store it |
| Execute mutation operator |
| If satisfied, then solution obtained |
| If the stopping criterion is not satisfied, go to step 5 |
Sharing content requires targeting cookies to be enabled. Please update your cookie preferences to use this feature.