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Simulation and optimisation based approach for job shop scheduling problems

机译:基于仿真和优化的车间作业调度方法

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This paper presents a hybrid Simulation based Optimization (SbO) approach to solve job shop scheduling problems. SbO structure for classical job shop scheduling introduced by [6] is extended for flexible job shop scheduling problem (FJSSP). Performance of SbO is bench-marked in terms of number of decision variables, constraints, objective value and computational time against various Mixed Integer Programming (MIP) based methods from literature. SbO outperforms for all the parameters and performs better with increasing problem size. Further, an hybrid solution architecture, Combined Simulation & Optimization (CSO) is introduced which integrates SbO and MIP to expedite the convergence to exact optimal solution. Results for CSO are also bench-marked against MIP based approaches, which shows that CSO performs better and converges faster.
机译:本文提出了一种基于仿真的混合优化(SbO)方法来解决作业车间调度问题。文献[6]引入的用于经典作业车间调度的SbO结构被扩展用于灵活的作业车间调度问题(FJSSP)。 SbO的性能在决策变量的数量,约束,目标值和计算时间方面相对于文献中基于各种混合整数编程(MIP)的方法而言是基准。 SbO的所有参数均胜过所有,并且随着问题规模的扩大而表现更好。此外,引入了混合解决方案体系结构,即组合模拟与优化(CSO),该体系将SbO和MIP集成在一起,以加快收敛到精确的最佳解决方案的速度。 CSO的结果也针对基于MIP的方法进行了基准测试,这表明CSO的性能更好,收敛速度更快。

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