Research on multi-object clonal genetic algorithm for the 0-1 knapsack

Immune clonal algorithm (ICA) is applied to genetic algorithm (GA) to develop a class of multi-object clonal genetic algorithm (MOCGA) for combinatorial optimization. With the condition of preserving simulated annealing advantages, MOCGA takes advantage of ICA algorithm so as to avoid premature convergence. To demonstrate its effectiveness and applicability, experiments are carried out on the 0-1 knapsack problem. The results show that MOCGA performs well, without premature convergence as compared to GA.