计算机工程与应用2011，Vol.47Issue(36)：57-60,64,5.DOI:10.3778/j.issn.1002-8331.2011.36.016
基于模拟退火选择的动态免疫算法及其应用
Dynamic immune algorithm based on simulated annealing selection and its application
摘要
Abstract
A novel dynamic immune optimization algorithm(DIASA),based on simulated annealing selection theory, adaptive memory and the functions of dynamic recognition of immune system, is proposed to solve the high-dimensional dynamic knapsack problem with constraints.The keys of algorithm are included: (l)The affinity of antibody is designed based on the performance of current population.(2)The infeasible antibodies are repaired by the increasing sorting of price consistency of antibodies gene,while the feasible antibodies are cloned and mutated dynamically,the mutation probability is designed by the density of antibody.(3)The new environmental population is generated using memory cells according to environmental recog nition operator, which accelerates the convergence of algorithm.In numerical experiments, two existing intelligent algorithms ETGA and ISGA for dynamic optimization problem are selected to compare with the algorithm designed for dynamic high dimension knapsack problem,the results indicate that the DIASA shows a promising convergent capability,and can track rap idly the optimum,powerful diversity of population.关键词
动态环境/动态背包问题/免疫算法/模拟退火选择/群体多样性Key words
dynamic environments/dynamic knapsack problem/immune algorithms/simulated annealing selection/population diversity分类
信息技术与安全科学引用本文复制引用
钱淑渠,武慧虹..基于模拟退火选择的动态免疫算法及其应用[J].计算机工程与应用,2011,47(36):57-60,64,5.基金项目
贵州省自然科学基金(No.20090074). （No.20090074）
