An improved method for solving the large-scale multidimensional 0-1 knapsack problem

In order to improve the searching performance and the efficiency for solving the large-scale multidimensional 0-1 knapsack problem, an improvedmethod based on genetic algorithm (lGA) which combines with pattern substitution and greedy algorithmis designed. The algorithm makespattern substitution thatthe excellent genes replacessomerelatively worse ones, then sortsthose individuals through the improved greedy thought, finally optimizes the solution by maximum repair strategy after a series of genetic operation such as crossover and mutation. The experiment results show that IGA improves the ability of searching optimization and convergence speed compared with simple genetic algorithm and greedy method genetic algorithm. On the problem of solving large-scale, IGAsignificantly improves the precision and stability compared with greedy algorithm.