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다국어 초록 (Multilingual Abstract)

This article introduces a new mixed integer linear programming model for the optimal scheduling of multistage polymer plants. Most commodity polymer plants are composed of three stages, viz. reaction, extrusion, and packaging. The operation of the reaction stage includes both batch processing, i.e., one process produces multiple products in a sequence, and continuous processing, i.e., the process runs continuously during product transition and the lot size for each product is variable. The operating mode of the extrusion and packaging stages are semicontinuous. The development of mixed integer linear programming models for optimizing a single production stage has been reported in the literature [1]. In this study, we modified the model to include the extrusion and packaging stages using simple assumptions. In the model M1 reported in [1], the parts that require the longest computing time determine the sequence of forecasting time zone and the production time. We replaced these parts with the specially ordered set function. The computing capability of the modified model was compared with that of the previously reported model M1 using input data collected from five actual polymer plants. Compared to the previously reported model M1, the proposed model showed better performance with a CPU time reduced to 70 % and the optimality gap reduced to 15 % on an average.

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목차 (Table of Contents)

Abstract
Ⅰ. 서론
Ⅱ. 문제설명
Ⅲ. 최적화 모형
Ⅳ. 실제 공장운전 자료를 이용한 성능비교

Abstract
Ⅰ. 서론
Ⅱ. 문제설명
Ⅲ. 최적화 모형
Ⅳ. 실제 공장운전 자료를 이용한 성능비교
Ⅴ. 결론
REFERENCES

참고문헌 (Reference)

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