摘要
文化基因算法是一种启发式算法,与一些经典数学方法相比,更适于求解多约束背包问题。文化基因算法是一种基于种群的全局搜索和基于个体的局部启发式搜索的结合体,针对多约束问题,提出采用贪婪策略通过违反度排序的方法处理多约束条件,全局搜索采用遗传算法,局部搜索采用模拟退火策略,解决具有多约束条件的0-1背包问题。通过对几个实例的求解,表明文化基因算法与标准遗传算法相比,具有更优的搜索性能。
Memetic algorithm is one of heuristic algorithms, it is more appropriate for multidimensional knapsack problems than some classical mathematical methods. It is a combination of global search based on populations and local search based on individuals. To the multidimensional problems, one approach is proposed using greedy strategy by sorting the degree of contravention, genetic algorithm is used for global search and simulated annealing is used for local search. The result of solving multidimensional 0 - l knapsack problems by memetic algorithm indicates that memetic algorithm can obtain better search performance than normal genetic algorithm,
出处
《计算技术与自动化》
2007年第4期61-63,67,共4页
Computing Technology and Automation
关键词
文化基因算法
背包问题
遗传算法
memetic algorithm
knapsack problems
genetic algorithm
