摘要
针对典型的组合优化问题——多选择背包问题(MCKP),提出了一种融合差异进化的混合算法(IDEHA)。算法按照适应度值将个体分为3个阶级,实施差异进化;通过设计一种有效的随机贪心修复策略,引入精英库进行协同寻优来加速算法收敛。通过对典型的多选择背包算例的求解并与其他算法的对比分析,基于融合差异进化的混合算法具有收敛速度快、求解精度高、稳定性和鲁棒性强等优点。
The multiple-choice knapsack problem(MCKP)is a kind of typical multi-constraint combinatorial optimization problem.In order to solve this kind of problem,a hybrid algorithm integrating differential evolution,named IDEHA,is proposed and designed.According to their fitness values,the proposed algorithm divides all the individuals into three classes to implement dif⁃ferential evolution.Through designing an effective random greedy repair strategy and introducing the elite database for collaborative optimization,the convergence of the proposed algorithm is speeded up.In comparison with the other algorithms through typical multi-choice knapsack examples,it is demonstrated that the proposed algorithm has the advantages of fast convergence speed,high solution accuracy,strong stability and robustness.
作者
蒋妍
潘大志
JIANG Yan;PAN Dazhi(School of Mathematics and Information,China West Normal University,Nanchong 637009)
出处
《计算机与数字工程》
2022年第4期744-749,共6页
Computer & Digital Engineering
基金
国家自然科学基金项目(编号:11871059)
四川省教育厅自然科学基金项目(编号:18ZA0469)
西华师范大学英才科研基金项目(编号:17YC385)资助。
关键词
个体差异进化机制
随机贪心修复策略
精英库
鱼群算法
粒子群算法
多选择背包问题
individual difference evolution mechanism
random greedy repair strategy
elite library
fish swarm algorithm
particle swarm optimization
multiple-choice knapsack problem