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基于改进遗传算法的车间调度优化及其仿真

The Optimization and Simulation on Shop Scheduling Problem Based on Improved Genetic Algorithm

【作者】 马秀明

【导师】 邢英杰;

【作者基本信息】 大连理工大学 , 工业工程, 2008, 硕士

【摘要】 随着全球经济一体化和企业间竞争的愈演愈烈,改善企业内部生产管理的生产调度技术受到了高度的重视,目前已产生了大量关于生产调度技术的理论研究成果,但是这些研究成果大多只是理论研究,并没有应用到实际生产当中。该文在将遗传算法改进的基础上,对流水车间调度、混合流水车间调度和作业车间调度分别做了算法设计,并通过Flexsim进行了系统仿真,真实地呈现了改进遗传算法实现的车间调度过程和合理性。该文首先对遗传算法做了大量的研究和分析,发现传统的遗传算法解决车间调度问题存在局部收敛和收敛概率偏低的问题,针对该问题提出了一种并行算法结构的改进遗传算法,该算法融入了动态自适应策略和混合启发式等方法,通过与传统遗传算法的对比验证了算法在保证局部搜索速度的前提下还尽可能的保证全局搜索,避免陷入局部最优,提高了最优率。在应用改进的遗传算法基础上,针对流水车间调度、混合流水车间调度和作业车间调度分别给出了不同的算法实现方案,并在算法实现的过程中做了适当的调整和改进,然后通过对经典调度模型、汽车发动机车间模型和机车厂车间模型实例化验证了算法实现的效果。最后实现了对流水车间调度、混合流水车间调度和作业车间调度的系统实现和Flexsim仿真,可动态地观察整个调度过程,进一步地证明了遗传算法在实际调度应用中的可行性和有效性。该文提出的改进遗传算法改善了遗传算法中收敛概率低的问题,目标函数能满足客户对车间调度现实问题的需要。应用改进遗传算法实现的车间调度系统和仿真对实际生产有一定的指导作用。

【Abstract】 Due to economic globalization and fierce competition in companies, optimizing shop scheduling of inner manufacturing management has played an important role. Now lots of theoretical investigation of shop scheduling has been done, however, most of them haven’t been applied in practical production. This thesis has optimized the traditional Genetic Algorithm (GA) to solve Flow Shop Scheduling Problem (FSP), Hybrid Flow-shop Scheduling Problem (HFSP) and Job Shop Scheduling Problem (JSSP). Flexsim software is used to simulate these problems. The simulation results prove that applying Improved Genetic Algorithm (IGA) to solve the shop scheduling problem is feasible and robust.Firstly, the thesis has improved upon the structure of GA to a parallel structure of algorithm aiming at the problem that GA is easy to run into local optima, appear premature convergence and has low probability of convergence after research and analysis. And the IGA, including dynamic self-adapting method and hybrid heuristic method, can search the global optimum rather than local optimum, and enhance the optimum rate based on fast searching rate.Secondly, the thesis has solved FSP, HFSP and JSSP by different implementation methods of IGA and optimized the procedure. This algorithm has some better results by means of vefifying the problem of the benchmarks of shop scheduling problem, automobile engine model and locomotive model.Finally, the thesis has established IGA procedure, designed a visual programming interface, and achieved dynamic simulation of Flexsim on FSP, HFSP and JSSP. The whole scheduling process of dynamic simulation can be observed, which proves the IGA feasible and efficient in practice.IGA could improve the problem of low probability of convergence. Objective function could fulfill the need of client on the shop scheduling. The paper is of profound practical significance.

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