Adaptive genetic annealing algorithm of solving 0/1 knapsack
求解0/1背包问题的自适应遗传退火算法

For the problem of premature convergence and slow convergence about the standard genetic algorithm, this paper proposes an adaptive genetic annealing algorithm used to slove the high-dimensional optimization constrained problem. It combines roulette with the optimal preservation strategy which combines adaptive crossover with mutation probability, then introduces simulated annealing algorithm so as to speed up the convergence rate of interactive post. Finally, the experiment compares the results of the two genetic algorithms and represents that adaptive genetic annealing algorithm is more accurate and efficient in resolving 0/1 knapsack problem.