摘要
为了进一步拓宽鸡群算法的研究领域,设计一种离散型鸡群算法(DCSO)。针对0-1背包问题的特点,在基本鸡群算法的基础上,对更新后的鸡群进行离散化处理,同时,在公鸡的位置更新过程中,引入自适应权重组合变异算子并动态调整变异权重,增强种群的多样性,更好地维持算法的"开采"与"搜索"两个阶段的平衡。最后,采用贪心修复算子对不可行解进行修正。通过4个经典0-1背包问题实例的仿真结果表明,相比离散粒子群算法、遗传算法和蚁群算法,DCSO算法在解的质量、收敛速度以及鲁棒性等方面效果显著提升,验证了该算法的可行性。
In order to further expand the research field of chicken swarm optimization,a discrete chicken swarm optimization(DCSO)algorithm is designed.According to the characteristics of the 0-1 knapsack problems,based on the chicken swarm algorithm,this paper discretes the updated chickens.At the same time,in the process of the rooster location update,this algorithm employs the adaptive weight combined mutation operator and adjusts the weight of mutation dynamically,enhances the diversity of population,better balances the"development"and"exploration"of the algorithm.Finally,greedy repair operator is used to modify the unfeasible solutions.Experiments are conducted on the 4 classical 0-1 knapsack problems,all results show that compared with discrete particle swarm optimization algorithm,genetic algorithm and ant colony algorithm,DCSO algorithm is improved significantly in the solution accuracy,convergence speed and robustness.The feasibility of this algorithm is verified.
作者
周洋
潘大志
ZHOU Yang;PAN Dazhi(College of Mathematic&Information,China West Normal University,Nanchong Sichuan 637000,China)
出处
《智能计算机与应用》
2019年第1期98-103,共6页
Intelligent Computer and Applications
基金
国家自然科学基金(11371015)
四川省教育厅自然科学基金(18ZA0469)
西华师范大学校级科研团队(CXTD2015-4)
西华师范大学英才基金(17YC385)
关键词
鸡群算法
0-1背包问题
离散化
自适应变异
chicken swarm algorithm
0-1 knapsack problem
discretization
adaptive mutation
