基于混合遗传算法的车间调度问题的研究

作业车间调度问题是最困难的组合优化问题之一，也是计算机集成制造系统中的一个关键环节，在实际生产中具有广泛应用。为此，提出了实现车间调度的混合遗传算法的设计方案，把遗传算法与模拟退火算法相结合，充分发挥遗传算法良好的全局搜索能力和模拟退火算法有效避免陷入局部极小的特性。通过实验验证了基于GASA混合算法的作业车间调度方法显著提高了搜索效率，改进了收敛性能。

Research on shop scheduling based hybrid- genetic algorithm

Job-shop Scheduling Problem (JSP) is one of the most difficult combinatorial optimization problems. It is one of the most important links on CIMS and widely applied to the engineering. This paper proposes a hybrid genetic algorithm to solve scheduling problem. To combine the genetic algorithm and simulated annealing, it is using GA excellent whole search ability and simulated annealing which is efficient to avoid getting into part minimum .The result of the test shows the efficiency of search is increased and the convergence is improved in shop scheduling with GASA hybrid algorithm.