Research on FJSP Problem of Invasive Weed Optimization Based on Hybrid Strategy

Authors

Li Ke, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Wang Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;

Abstract

Abstract: 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.

Recommended Citation

Ke, Li; Yan, Wang; and Ji, Zhicheng (2019) "Research on FJSP Problem of Invasive Weed Optimization Based on Hybrid Strategy," Journal of System Simulation: Vol. 30: Iss. 5, Article 38.
DOI: 10.16182/j.issn1004731x.joss.201805038
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss5/38

First Page

1918

Revised Date

2017-08-14

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201805038

Last Page

1926

CLC

TP391.9

Recommended Citation

Li Ke, Wang Yan, Ji Zhicheng. Research on FJSP Problem of Invasive Weed Optimization Based on Hybrid Strategy[J]. Journal of System Simulation, 2018, 30(5): 1918-1926.

DOI

10.16182/j.issn1004731x.joss.201805038