CAJ | 학술논문

针对现有和声搜索算法存在的不足,提出一种学习型和声搜索算法(LHS).根据目标函数值的变化,自适应调整和声记忆考虑概率(HMCR);引入学习机制,加快算法的搜索速度;动态调节基音调整概率(PAR),增强算法的全局搜索能力.对16个标准函数的测试结果表明,所提出的LHS算法与其他4种和声搜索算法相比具有较好的效果.最后将改进算法应用于10个0-1背包问题和1个经典的50维背包实例,实验结果表明LHS算法优于其他算法.关键词:和声搜索算法;自适应;学习策略;搜索速度;0-1背包问题
침대현유화성수색산법존재적불족,제출일충학습형화성수색산법(LHS).근거목표함수치적변화,자괄응조정화성기억고필개솔(HMCR);인입학습궤제,가쾌산법적수색속도;동태조절기음조정개솔(PAR),증강산법적전국수색능력.대16개표준함수적측시결과표명,소제출적LHS산법여기타4충화성수색산법상비구유교호적효과.최후장개진산법응용우10개0-1배포문제화1개경전적50유배포실례,실험결과표명LHS산법우우기타산법.관건사:화성수색산법;자괄응;학습책략;수색속도;0-1배포문제
For the purpose of avoiding the disadvantage of harmony search algorithm, a learned harmony search(LHS) algorithm is proposed. The adaptive parameter harmony memory consideration rate(HMCR) is designed based on the change of objective function value and the learning strategy is used to accelerate the speed of search. Then pitch adjustment rate(PAR) is adjusted dynamically to enhance the global search. The 16 classic test functions are tested, and the results show that LHS algorithm outperforms the other four harmony search algorithms. Finally, LHS algorithm is applied to 10 0-1 knapsack problems and a classic knapsack example, and the result shows that LHS algorithm is better than other algorithms.