Improved Intrusion Weed Algorithm for Solving Flexible Job Shop Scheduling Problem

Authors

Zhang Xin, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Li Ke, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Dahu Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: An improved invasive weed optimization algorithm is proposed for solving multi-objective flexible job shop scheduling problem (FJSP) with released time and delivery date. The minimum completion time of jobs, the maximum work load of machines and the total work load of all machines are taken as the optimization goals to establish a FJSP model. A random key encoding scheme based on transformed sequences is proposed and a mapping relationship is set up between the continuous space and the discrete space of FJSP. An adaptive Gauss mutation operator is introduced to diversify the population in the process of weed breeding. In spatial diffusion stage, the principle of Levy flight is taken to improve the global search ability, which contributes to escape from local optimal solution. The algorithm is compared with other different algorithms and the statistical results show that the algorithm is effective for solving the multi-objective FJSP.

Recommended Citation

Xin, Zhang; Ke, Li; Yan, Dahu; and Ji, Zhicheng (2019) "Improved Intrusion Weed Algorithm for Solving Flexible Job Shop Scheduling Problem," Journal of System Simulation: Vol. 30: Iss. 11, Article 50.
DOI: 10.16182/j.issn1004731x.joss.201811050
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss11/50

First Page

4469

Revised Date

2018-07-05

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201811050

Last Page

4476

CLC

TP391.9

Recommended Citation

Zhang Xin, Li Ke, Yan Dahu, Ji Zhicheng. Improved Intrusion Weed Algorithm for Solving Flexible Job Shop Scheduling Problem[J]. Journal of System Simulation, 2018, 30(11): 4469-4476.

DOI

10.16182/j.issn1004731x.joss.201811050