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.
出处
《价值工程》
2013年第22期231-232,共2页
Value Engineering
关键词
背包问题
遗传算法
鲁棒性
贪婪算法
knapsack problem
genetic algorithm
robustness
greedy algorithm
