| (1) Encode the parameters for the partitioning problem; |
| (2) Initialize the first generation ; |
| (3) Calculate the fitness of each individual in ; |
| (4) Copy the individual with the highest fitness to the solution; |
| (5) while (termination conditions) do |
| (6) while (number of individuals generation size) do |
| (7) Select two individuals ; |
| (8) Perform crossover on ; |
| (9) if (max{fitness(), fitness()} max{fitness(), fitness()}) then |
| (10) Reject the crossover with ; |
| (11) else |
| (12) Accept the crossover; |
| (13) end if |
| (14) Perform mutation on to produce ; |
| (15) if (fitness() fitness()) then |
| (16) Reject the mutation, ; |
| (17) else |
| (18) Accept the mutation; |
| (19) end if |
| (20) Perform the above steps on to produce ; |
| (21) end while |
| (22) Calculate the fitness of each individual; |
| (23) if (the highest fitness fitness(solution)) then |
| (24) Copy the individual with the highest fitness; |
| (25) end if |
| (26) increase the generation number; |
| (27) end while |
| (28) return solution: , ; |
