지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems Vol.20 No.4
- 발행연도
- 2021.12
- 수록면
- 596 - 603 (8page)
- DOI
- 10.7232/iems.2021.20.4.596
이용수
초록· 키워드
오류제보하기
Nowadays, it is necessary to paying attention to the opportunities and threats in the field of industry and trade, and evaluate the ability of industries and companies in dealing with uncertainties and existing risks, and it is very important to manage supply chain risk. The main purpose of this study is to be careful against risky suppliers and reducing the injury rate in the event of a disruption. Therefore, in this regard, a multi-stage mixed integer programming model with a proactive approach has been used; that in the first stage, the model reports the amount of supply from suppliers without considering the risk criterion, and at the same time, it seeks to optimal state of minimization the supply chain costs (including purchase cost, shipping, maintenance, supplier selection and return goods). In the second stage, after the suppliers which supplying the parts, have been identified, the model seeks to minimize the identified risks of suppliers under different scenarios. In the third stage, the model tries to achieve an optimal state of supplying the parts from less risky suppliers. In the continuation of this study, an integrated multi-objective programming model has been designed, which will be solved by the epsilon constraint method, and the best output will be reported from the Pareto’s optimal set of answers; Finally the results of the model will be compared in two multi-stage and integrated multi-objective modes and the correctness of the performance is confirmed.
목차
ABSTRACT
1. INTRODUCTION
2. PROBLEM DEFINITION
3. RESULTS
4. CONCLUSION
REFERENCES
참고문헌 (9)
참고문헌 신청
Christopher, M. / Understanding supply chain risk: A self-assessment workbook
Hosseini, S. / 2020 / Bayesian networks for supply chain risk, resilience and ripple effect analysis : A literature review / Expert Systems with Applications 161:113649
Kirilmaz, O. / 2017 / A proactive approach to supply chain risk management : Shifting orders among suppliers to mitigate the supply side risks / Journal of Purchasing and Supply Management 23(1):54~65
Kleindorfer, P. R. / 2005 / Managing disruption risks in supply chains / Production and Operations Management 14(1):53~68
Munir, M. / 2020 / Supply chain risk management and operational performance : The enabling role of supply chain integration / International Journal of Production Economics 227:107667
Hosseini, S. / 2020 / Bayesian networks for supply chain risk, resilience and ripple effect analysis : A literature review / Expert Systems with Applications 161:113649
Kirilmaz, O. / 2017 / A proactive approach to supply chain risk management : Shifting orders among suppliers to mitigate the supply side risks / Journal of Purchasing and Supply Management 23(1):54~65
Kleindorfer, P. R. / 2005 / Managing disruption risks in supply chains / Production and Operations Management 14(1):53~68
Munir, M. / 2020 / Supply chain risk management and operational performance : The enabling role of supply chain integration / International Journal of Production Economics 227:107667
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