Hybrid Flow-Shop Scheduling Method and Simulation Based on Adaptive Genetic Algorithm
2014 ◽
Vol 670-671
◽
pp. 1434-1438
Keyword(s):
The n-job, k-stage hybrid flow shop problem is one of the general production scheduling problems. Hybrid flow shop (HFS) problems are NP-Hard when the objective is to minimize the makespan .The research deals with the criterion of makespan minimization for the HFS scheduling problems. In this paper we present a new encoding method so as to guarantee the validity of chromosomes and convenience of calculation and corresponding crossover and mutation operators are designed for optimum sequencing. The simulation results show that the Sequence Adaptive Cross Genetic Algorithm (SACGA) is an effective and efficient method for solving HFS Problems.
2013 ◽
Vol 753-755
◽
pp. 2925-2929
2015 ◽
Vol 766-767
◽
pp. 962-967
2015 ◽
Vol 28
(8)
◽
pp. 1915-1931
◽
2006 ◽
Vol 2006
◽
pp. 1-17
◽