基于混合遗传禁忌的多目标柔性作业车间调度

Multi-Objective Flexible Job-Shop Scheduling Problem Based on Compound Gene and Tabu Algorism

针对多目标柔性作业车间调度问题(Flexible job-shop scheduling problem,FJSP),提出了一种结合遗传算法和禁忌算法求解FJSP的调度算法。首先,定义了FJSP问题模型,然后提出采用改进的遗传算法对其进行求解,采用双链进行染色体编码和NEH方法获得初始解,并提出了自适应的选择策略、混合交叉策略和复合变异策略以实现个体保优和更新,当遗传算法陷入局部最优解时,采用禁忌算法跳出局部最优,以实现全局最优解的获取。仿真实验证明文中的方法能有效地解决FJSP问题,获得全局最优解,且与其他方法相比,文中方法具有收敛速度快和求解效率高的优势。

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.