author Hanil Jeong 
2nd author / Kidong Kim (Dept. of Industrial Engineering, Seoul National University)
/ Chankwon Park (Dept. of Industrial Engineering, Seoul National University)
/ Jinwoo Park (Dept. of Industrial Engineering, Seoul National University)
/ Seongyoung Jang (Dept. of Industrial Engineering, Seoul National University) 
info Date: 1996년 10월 29일 ~ 1996년 10월 31일
City: Seoul
Nation: Korea
Additional Information: Vol. I, 337-342 
year 1996 
category IC 
start / end date  
city / nation  
학회 PCM 
keywords Batch Splitting, Branch and Bound, Job Shop Schuduling 
abstract The job shop scheduling problem has been a major target for many researchers. Unfortunately, though, most of the past studies assumed that a job consists of only a single part. However, if we assume that a job consists of a batch as in many real manufacturing environment, and allow each part to be processed independently, then we can obtain an improved schedule because we can fill up the idle times of machines with jobs of smaller processing times. However, then, the size of the scheduling problem would become too large to be solved in practical time limit, and the clerical work will also increase to handle the increased number of production orders. And so, there may be an optimum batch size considering trade-off between better solution and tractability. Current study is the result of an attempt to find an acceptable solution when the production requirement from MRP(material requirement planning) system for a planning period exceeds the capacity of production system. We try to get an improved schedule by splitting the original batch into smaller batches, and thereby meet the due date requirement without resorting to rescheduling of the master production schedule. For the given batch, we disaggregate the job processing time into smaller chunks according to the algorithm we are proposing. And then, a new branch and bound algorithm is applied to solve the transformed job shop scheduling problem. It also turned out that we can adapt to unexpected dynamic events more elegantly by allowing batch splitting. Experimental results are included to show the computational characteristics of the proposed approach and the efficiency of the proposed algorithm. 


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