TY - GEN
T1 - An Improved Genetic Algorithm Based on Neighborhood Search for Flexible Job-shop Scheduling problem
AU - Yan, Ge
AU - Zijin, Zhao
AU - Aimin, Wang
AU - Jieran, Ye
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/9
Y1 - 2019/5/9
N2 - To deal with the flexible job-shop scheduling problem (FJSP), an improved genetic algorithm based on neighborhood search is proposed. The algorithm adds the design of neighborhood search compared with the traditional GA, which makes the general individuals in the population approach the neighborhood which tending to the excellent individuals, and accelerates the local search ability of the algorithm. Large-scale mutation is also designed in the algorithm to make the population be redistributed in the solution space when falling into local optimum, and find the next local optimum solution, thus find the global optimum solution in multiple local optimum solutions. Finally, a program was developed with the actual data of a workshop to verify the feasibility and effectiveness of the algorithm. The result shows that the algorithm achieves satisfactory results in all indexes mentioned above.
AB - To deal with the flexible job-shop scheduling problem (FJSP), an improved genetic algorithm based on neighborhood search is proposed. The algorithm adds the design of neighborhood search compared with the traditional GA, which makes the general individuals in the population approach the neighborhood which tending to the excellent individuals, and accelerates the local search ability of the algorithm. Large-scale mutation is also designed in the algorithm to make the population be redistributed in the solution space when falling into local optimum, and find the next local optimum solution, thus find the global optimum solution in multiple local optimum solutions. Finally, a program was developed with the actual data of a workshop to verify the feasibility and effectiveness of the algorithm. The result shows that the algorithm achieves satisfactory results in all indexes mentioned above.
KW - global optimal solution
KW - local optimal solution
KW - neighborhood search
KW - scheduling
UR - http://www.scopus.com/inward/record.url?scp=85066466073&partnerID=8YFLogxK
U2 - 10.1109/ICMIMT.2019.8712021
DO - 10.1109/ICMIMT.2019.8712021
M3 - Conference contribution
AN - SCOPUS:85066466073
T3 - 2019 IEEE 10th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2019
SP - 142
EP - 146
BT - 2019 IEEE 10th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2019
Y2 - 15 February 2019 through 17 February 2019
ER -