结合遗传算子的并行萤火虫算法及在车间调度中的应用  

A Parallel Firefly Algorithm Combined with Genetic Operator and Its Application on Shop Scheduling

作　　者：周艳平[1] 刘永娟 ZHOU Yanping;LIU Yongjuan(College of Information Science and Technology,Qingdao University of Science&Technology,Qingdao 266061)

机构地区：[1]青岛科技大学信息科学技术学院,青岛266061

出　　处：《计算机与数字工程》2024年第5期1388-1393,共6页Computer & Digital Engineering

摘　　要：论文提出了一种结合遗传算子的并行萤火虫算法,该算法借鉴了萤火虫闪烁移动的思想,对两个种群进行同步并行迭代求解,以提升算法的求解速度和质量;在其中一个种群中引入多尺度协同变异算子,利用不同大小方差的自适应高斯变异机制使整个种群以尽量分散的变异尺度来对解空间进行更详尽的探索,从而使整个种群进行有效变异。函数优化结果表明了该算法的有效性,该算法用于求解以最小化最大完工时间为优化目标的流水车间调度问题,实验结果表明,较传统的单一算法而言,结合遗传算子的并行萤火虫算法在求解车间调度问题方面具有更好的性能。A parallel firefly algorithm combined with genetic operator is proposed,which is based on the idea of firefly flicker-ing and moving,and synchronizes parallel iterative solutions for two populations to improve the solving speed and quality of the algo-rithm.A multi-scale cooperative mutation operator is introduced in one of the populations,and the adaptive Gaussian variation mechanism with different variances is used to promote the entire population to explore the solution space in detail at as dispersed variation scales as possible,so that the entire population can undergo effective variation.The function optimization results show the effectiveness of the algorithm,this algorithm is used to solve flow shop scheduling problems with minimizing the maximum comple-tion time as the optimization objective,the experimental results show that compared with the traditional single algorithm,the paral-lel firefly algorithm combined with genetic operators has better performance in solving the shop scheduling problem。

关 键 词：萤火虫算法 多尺度协同变异算子 并行算法 流水车间调度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]