Novel firefly algorithm for solving Job Shop scheduling problem

Abstract

Abstract: Job-shop scheduling problem is a problem with high research and engineering application value. The paper presents a new novel algorithm（firefly algorithm） for solving job-shop scheduling problem and analyzes the bionic principle, then lists the solving steps using FA. Compared with GA and PSO, the simulation results for benchmark instances verify that firefly algorithm shows merits of fewer parameters, simple operation and fast convergence.

Key words: job-shop scheduling, firefly algorithm, bionics

摘要： Job shop调度问题是一类具有很高理论研究和工程应用价值的问题。针对该问题提出一种新型萤火虫求解算法，分析了萤火虫算法的仿生原理，给出了萤火虫算法求解JSP问题的求解步骤，并通过典型基准测试实例对算法进行了仿真实验，并与GA和PSO算法进行了比较，验证了该算法参数少，操作简单，收敛速度快，在生产调度中有广泛的应用前景。

关键词: 作业车间调度问题, 萤火虫算法, 仿生原理

YANG Jiao, YE Chunming. Novel firefly algorithm for solving Job Shop scheduling problem[J]. Computer Engineering and Applications, 2013, 49(11): 213-215.

杨娇，叶春明. 应用新型萤火虫算法求解Job-shop调度问题[J]. 计算机工程与应用, 2013, 49(11): 213-215.

[1]	ZHANG Zhechen，LIU Sanyang. Firefly Algorithm Based on Topology Improvement and Crossover Strategy [J]. Computer Engineering and Applications, 2019, 55(7): 1-8.
[2]	YAN Xu, YE Chunming. Hybrid Grasshopper Optimization Algorithm for Job-Shop Scheduling Problem [J]. Computer Engineering and Applications, 2019, 55(6): 257-264.
[3]	ZHU Dan1, QIU Bin1，2, XIAO Hailin1，4, NI Ju3. Spectrum Allocation in Cognitive Vehicular Network Based on Firefly Algorithm [J]. Computer Engineering and Applications, 2019, 55(2): 67-71.
[4]	JU Luyan1, YANG Jianjun2, ZHANG Jianbing1, GUO Longlong1, LI Suobin1. Improved NSGA for Multi-Objective Flexible Job-Shop Scheduling Problem [J]. Computer Engineering and Applications, 2019, 55(13): 260-265.
[5]	LI Fan1, GAO Dong1, XU Xin2, ZHANG Yuliang2. Research of improved bat algorithm for flexible job-shop scheduling problem [J]. Computer Engineering and Applications, 2018, 54(21): 265-270.
[6]	LI Lina1, GUO Yongqiang1，2, ZHANG Xiaodong1, LU Yuan1, XU Panfeng1. Path planning algorithm for robot based on firefly algorithm combined with artificial potential field method [J]. Computer Engineering and Applications, 2018, 54(20): 104-109.
[7]	QU Chiwen1, FU Yanming2, LUO Mingshan1, LIN Chengde1, HE Wei1. Solving flexible job-shop scheduling problem using bird swarm algorithm [J]. Computer Engineering and Applications, 2018, 54(17): 249-257.
[8]	CHEN Guanyu1, SUN Peng1，2, ZHANG Jieyong1, WU Junsheng3. Adaptive adjustment of command and control structure based on discrete firefly algorithm [J]. Computer Engineering and Applications, 2018, 54(15): 112-119.
[9]	DUAN Shaonan, DAI Shenghua. Application of discrete firefly algorithm in high-speed train operation adjustment [J]. Computer Engineering and Applications, 2018, 54(15): 209-213.
[10]	YANG Yujun, CHEN Ye. Hybrid ant colony optimization for flexible robotic manufacturing cell scheduling problem [J]. Computer Engineering and Applications, 2018, 54(13): 160-167.
[11]	YANG Xiaodong, KANG Yan, LIU Qing, Sun Jinwen. Tabu estimation of distribution algorithm for job-shop scheduling problem [J]. Computer Engineering and Applications, 2017, 53(7): 147-153.
[12]	ZHANG Ming, ZHANG Shuqun, LEI Zhaoyi. Application of improved firefly algorithm in neural network [J]. Computer Engineering and Applications, 2017, 53(5): 159-163.
[13]	BAO Xiaoxiao1, YE Chunming1, HUANG Xia1，2. Solving job-shop scheduling problem by firework algorithm [J]. Computer Engineering and Applications, 2017, 53(3): 247-252.
[14]	SHI Wenzhang1, HAN Wei1, DAI Ruiwen2. Modified cuckoo search algorithm for job-shop scheduling problem based on simulated annealing [J]. Computer Engineering and Applications, 2017, 53(17): 249-253.
[15]	WANG Meng, FAN Kun, ZHAI Yafei, LI Xinning. Study of multiprocessor task scheduling problem in network parallel computing system [J]. Computer Engineering and Applications, 2017, 53(10): 264-270.

Novel firefly algorithm for solving Job Shop scheduling problem

应用新型萤火虫算法求解Job-shop调度问题

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics