摘要
为了更加有效地求解柔性作业车间调度问题,提出一种混合策略的入侵杂草算法。在种子繁殖阶段,通过引入自适应高斯变异算子增加种群多样性。在扩散阶段,采用基于正切函数的正态分布标准差作为种子新的步长搜索方式。在竞争生存阶段,利用蜂群算法中的引导搜索策略对杂草个体进行引导搜索,以提高其跳出局部最优的能力。提出一种基于转化序列的随机键编码方式,并将所提算法通过实例与其他算法进行仿真实验对比,统计结果表明所提算法具有更好的收敛性,适合解决该类调度问题。
To solve the flexible job-shop scheduling problem more effectively, an improved invasive weed algorithm was proposed. A random key encoding scheme based on transformed sequences was proposed and an adaptive Gauss mutation operator was introduced to diversity the population in the process of weed breeding. In spatial diffusion stage, the standard deviation of normal distribution based on tangent function was used as seed＇s new step size search method. In competition of invasive weed stage, by using the guided search strategy in the bee colony algorithm, the weed was guided to improve its ability to jump out of the local optimum. A random key encoding scheme based on transformed sequences was proposed. The proposed algorithm was compared with other different algorithms, the statistical results show that proposed algorithm has better convergence than other algorithms for solving the scheduling problem.
作者
李珂
王艳
纪志成
Li Ke;Wang Yan;Ji Zhicheng(Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2018年第5期1918-1926,共9页
Journal of System Simulation
基金
国家自然科学基金(61572238)
江苏省杰出青年基金(BK20160001)
