%0 Journal Article
%T Adaptive genetic annealing algorithm of solving 0/1 knapsack<br>求解0/1背包问题的自适应遗传退火算法
%A LV Xueqin
%A CHEN Shuguo
%A LIN Jing
%A <br>吕学勤
%A 陈树果
%A 林静
%J 重庆邮电大学学报(自然科学版)
%D 2013
%I 
%X 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.
%K genetic algorithm
%K optimization problem
%K simulated annealing
%K 0/1 knapsack
%K adaptive genetic annealing algorithm<br>遗传算法
%K 优化问题
%K 模拟退火
%K 0/1背包
%K 自适应遗传退火算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=96E6E851B5104576C2DD9FC1FBCB69EF&jid=5C2694A2E5629ECD6B59D7B28C6937AD&aid=1D447377FA3F59D0EB730434AC36374A&yid=FF7AA908D58E97FA&iid=CA4FD0336C81A37A&sid=09E495F616948E78&eid=E22B6B8FE86DD8F9&journal_id=1673-825X&journal_name=重庆邮电大学学报(自然科学版)&referenced_num=0&reference_num=0