%0 Journal Article
%T Multi-Objective Flexible Job-Shop Scheduling Problem Based on
%A MO Jian-lin
%A WU Zhe
%J Journal of Chongqing Normal University
%D 2013
%I Chongqing Normal University
%X Aiming at the solving FJSP (Flexible job-shop scheduling problem), a scheduling algorism combined gene and tabu algorism were proposed. Firstly, the FJSP problem model was defined, then the improve gene algorism was used to obtain the solution, the chromosome was coded as double-stranded and the NEH algorism was used to get the initial solution. And the adaptive selection strategy, compound cross strategy and mutation strategy were introduced to protect the optimum chromosome and renew. When the gene algorism got the local optimum solution, the tabu algorism was used to get the global solution. The simulation experiment shows our method in this paper can resolve the FJSP effectively and get the optimal solution, compared with the other methods; the method has the rapid convergence and high solution efficiency.
%K flexible job-shop scheduling problem
%K Tabu search
%K multi-goal
%K gene algorism
%U http://journal.cqnu.edu.cn/1302/pdf/130220.pdf