پیش‌بینی اختلالات زنجیره تأمین به کمک داده‌کاوی در مسیر پایداری و هوش مصنوعی

•   آرشیو : نسخه بهار1404
•   کد پذیرش : 12421
•   موضوع : موضوعی تعریف نشده!
• نویسنده/گان : | سعیده نادری
•   زبان : فارسی
•   نوع مقاله : پژوهشی
•   چکیده مقاله به فارسی : در دنیای پیچیده و همیشه در حال تغییر امروز، نگرانی‌ها در مورد کمبود داده‌های کافی با نگرانی‌ها در مورد داده‌های بیش از حد برای مدیریت زنجیره تامین (SCM) جایگزین شده است. (حجم داده‌های تولید شده از تمام بخش‌های زنجیره تأمین، ماهیت تحلیل SCM را تغییر داده است. با افزایش حجم داده‌ها، کارایی و اثربخشی روش‌های سنتی کاهش یافته است. محدودیت‌های این روش‌ها در تجزیه و تحلیل و تفسیر حجم زیادی از داده‌ها، محققان را بر آن داشته تا روش‌هایی تولید کنند که توانایی بالایی در تجزیه و تحلیل و تفسیر کلان داده‌ها دارند. شناخته‌شده‌ترین تکنیک‌های هوش مصنوعی (AI) با توسعه یک چارچوب مفهومی، مشارکت تکنیک‌های ML در انتخاب و تقسیم‌بندی تامین‌کنندگان، پیش‌بینی ریسک‌های زنجیره تامین، و تخمین تقاضا و فروش، تولید، مدیریت موجودی، حمل‌ونقل و توزیع، توسعه پایدار (SD) و اقتصاد دایره‌ای (CE) و محدودیت‌ها را مورد بحث قرار می‌دهد. جهت‌های تحقیقاتی آتی داده شده است.
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•   کلمات کلیدی به فارسی : الگوریتم یادگیری ماشین، الگوریتم، اختلال زنجیره تأمین، داده کاوی، پایداری.
•   چکیده مقاله به انگلیسی : In today's complex and ever-changing world, concerns about not having enough data have been replaced by concerns about too much data for supply chain management (SCM). The volume of data generated from all parts of the supply chain has changed the nature of SCM analysis. As the volume of data increases, the efficiency and effectiveness of traditional methods have decreased. The limitations of these methods in analyzing and interpreting large volumes of data have prompted researchers to develop methods that have a high ability to analyze and interpret big data. The most well-known artificial intelligence (AI) techniques are discussed by developing a conceptual framework, the contribution of ML techniques in supplier selection and segmentation, supply chain risk prediction, and demand and sales estimation, manufacturing, inventory management, transportation and distribution, sustainable development (SD), and circular economy (CE) and limitations. Future research directions are given.
•   کلمات کلیدی به انگلیسی : Machine learning algorithm, algorithm, supply chain disruption, data mining, sustainability.
•  صفحات : 15-32
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