| Summary: | 碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 98 === Production scheduling problems is a very important topic in production management. Most of the reality of scheduling is difference to scheduling theory, because real-world manufacturing usually operate in highly uncertain environments. This study deals with the single machine scheduling problem (SMSP) with uncertain job processing times. The objective is to obtain robust job sequences with minimum worst-case mean tardiness among a set of possible scenarios. We proposed a RCO formulation based on the idea of Bertsimas and Sim, and this RCO formulation can be reformulated as a mixed integer linear (MILP) program.The experiment of this study using the Forward Scheduling(FS) and Iterated Iterated Greedy Algorithm(IG) combined with robust scheduling, coding and implementation. We divide the number of the jobs into two different size problems of small size and large size. Furthermore, we analysis and test the experiment by FS and IG obtain the data. Experimental results demonstrate that the solutions of using FS and IG are approximately consistent with the optimal solution and very light computational efforts in small-sized problems. With the increase in the number of jobs, that the solution obtained with FS and IG is small gap, but it’s efficient in solving with IG. in the computation time. Therefore, using robustness to do scheduling not only steady the quality of the solution but also requires light computation time within the uncertainty problems. Should be continued research in future and application to production scheduling.
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