基于贪婪算法的改进自适应遗传算法及其应用

摘要

本文将改进的自适应遗传算法和贪婪算法相结合用于0-1背包问题的求解。此算法对交叉率和变异率进行了优化，实现了交叉率和变异率的非线性自适应调整，并对不可行解进行了贪婪修复。实验结果表明，相比传统的自适应遗传算法，新算法收敛速度快，寻优能力强，具有更可靠的稳定性。%This paper combines the improved adaptive genetic algorithm with greedy algorithm to solve the 0-1 knapsack problem. By optimizing the cross-over rate and mutation rate, this algorithm has realized non-linear adaptive adjustment, and has done greedy repair to the non-feasible solution. The result shows that, compared with traditional adaptive genetic algorithm, the new algorithm has faster convergence speed and stronger searching ability and more reliable stability.