نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشیار گروه مدیریت صنعتی- دانشکده اقتصاد ومدیریت و حسابداری دانشگاه یزد
2 استادیار گروه مدیریت صنعتی دانشکده اقتصاد ، مدیریت و حسابداری دانشگاه یزد
3 دانشجوی کارشناسی ارشد مدیریت گردشگری دانشگاه علامه طباطبائیی
چکیده
امروزه مدیریت زنجیر هى تأمین ب هدلیل جهان یشدن بازارهای کس بوکار، اهمیت بیشتری پیدا کرده
است. با افزایش پیچیدگی، سطح نبود اطمینان و ریسک موجود در زنجیره نیز افزایش م ییابد. از ای نرو
مدیریت ریسک زنجیر هى تأمین یکی از موضوعاتی است که مورد توجه سازما نها قرار گرفته است. یکی
از خطرهای موجود در زنجیر هى تأمین، ریس کهای وارده از ناحی هى تأمی نکنندگان است. تحقیق حاضر
با ب هکارگیری شبک ههای عصبی مصنوعی ب هعنوان ابزارى قدرتمند در پردازش اطلاعات غیرخطی، مدلی
مناسب براى پی شبینى ریسک وارده از سوى تأمی نکنندگان در شرکت فولاد آلیاژى ایران ارائه م ىدهد. در
این مدل با استفاده از تکنیک دلفى فازى هفت عامل ب هعنوان عوامل ورودی مدل شبک هى عصبى انتخاب
VIKOR و AHP شدند. براى محاسب هى میزان ریسک وارده از سوى هر تأمی نکننده، از تلفیق تکنیک
استفاده شده و با ب هکارگیرى مدل پرسپترون چندلایه، میزان ریسک وارده از سوى هر تأمی نکننده
پی شبینی شده است. در پایان با استفاده از تحلیل حساسیت تأثیر هرکدام از متغیرهای ورودی بر خروجی
ارزیابی و پیشنهاداتى براى کاهش ریسک ارائه شده است.
کلیدواژه‌ها
عنوان مقاله [English]
Developing an integrated model for evaluation Risk in Supply Chain using ANN (Case Study: Iran Alloy Steel Company)
نویسندگان [English]
- Seyed Habib Allah Mirghafoori 1
- Ali Morovati Sharifabadi 2
- Faezeh Asadian Ardakani 3
1 Associate Professor of industrial management, Yazd University
2 Assistant Professor of industrial management, Yazd University
3 Ph.D. Student of Tourism Management, Allameh Tabataba’i University
چکیده [English]
In the last few years, supply chain management becomes more important,
because of the globalization of business. By increasing complexity, level
of uncertainty and risk in the chain goes up. Hence supply chain risk management
has become a major issue in the organization. One of the risks
existing in the supply chain is risk of suppliers. This research provides
model for predicting supplier risk in Iran Alloy Steel Company that is then
analyzed using Artificial Neural Networks which are capable to consider
non-liner interrelations among criteria. In the model using fuzzy Delphi,
seven criteria have been identified. Then by using AHP-VIKOR the risk of
supplier calculated and the risk of suppliers were predicted. Finally, we use
sensitive analysis for identification effect of every input on output
کلیدواژه‌ها [English]
- Supplier Risk
- Fuzzy Delphi
- AHP-VIKOR
- Artificial Neural
- Network
- Sensitivity Analysis
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