☑️𝘿𝙖𝙩𝙖-𝘿𝙧𝙞𝙫𝙚𝙣 𝘿𝙞𝙨𝙩𝙧𝙞𝙗𝙪𝙩𝙞𝙤𝙣𝙖𝙡𝙡𝙮 𝙍𝙤𝙗𝙪𝙨𝙩 𝙊𝙥𝙩𝙞𝙢𝙞𝙯𝙖𝙩𝙞𝙤𝙣
[𝕟𝕖𝕨 𝕔𝕠𝕦𝕣𝕤𝕖 𝕚𝕟 Pᴇʀꜱɪᴀɴ]


👨‍💻 یک دوره فوق‌تخصصی در کلاس جهانی | زمستان امسال
🗓 مهلت ثبت‌نام: ۱۰ دی‌ماه
⚠️ ظرفیت خیلی محدود (به هدف تعامل بیشتر در کلاس)
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❓جزئیات بیشتر: @Ali_Papirad
✔️ثبت‌نام: @sms_optimyar
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◆ 𝘍𝘰𝘶𝘯𝘥𝘢𝘵𝘪𝘰𝘯𝘴 𝘰𝘧 𝘚𝘵𝘰𝘤𝘩𝘢𝘴𝘵𝘪𝘤 𝘗𝘳𝘰𝘨𝘳𝘢𝘮𝘮𝘪𝘯𝘨, 𝘙𝘰𝘣𝘶𝘴𝘵 𝘖𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯, 𝘢𝘯𝘥 𝘋𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯𝘢𝘭 𝘙𝘰𝘣𝘶𝘴𝘵𝘯𝘦𝘴𝘴
Conceptual frameworks, uncertainty modeling, and comparative perspectives
◆ 𝘋𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯𝘢𝘭𝘭𝘺 𝘙𝘰𝘣𝘶𝘴𝘵 𝘖𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯 (𝘋𝘙𝘖): 𝘔𝘰𝘥𝘦𝘭𝘴, 𝘊𝘭𝘢𝘴𝘴𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯𝘴, 𝘢𝘯𝘥 𝘋𝘢𝘵𝘢-𝘋𝘳𝘪𝘷𝘦𝘯 𝘗𝘦𝘳𝘴𝘱𝘦𝘤𝘵𝘪𝘷𝘦𝘴
From classical formulations to modern learning-based approaches
◆ 𝘋𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯𝘢𝘭 𝘈𝘮𝘣𝘪𝘨𝘶𝘪𝘵𝘺 𝘚𝘦𝘵𝘴 (𝘋𝘈𝘚) 𝘧𝘰𝘳 𝘋𝘙𝘖
Construction principles, statistical guarantees, and modeling trade-offs
◆ 𝘞𝘢𝘴𝘴𝘦𝘳𝘴𝘵𝘦𝘪𝘯 𝘋𝘙𝘖: 𝘛𝘩𝘦𝘰𝘳𝘺, 𝘙𝘦𝘧𝘰𝘳𝘮𝘶𝘭𝘢𝘵𝘪𝘰𝘯𝘴, 𝘢𝘯𝘥 𝘗𝘳𝘢𝘤𝘵𝘪𝘤𝘢𝘭 𝘔𝘰𝘥𝘦𝘭𝘪𝘯𝘨
Optimal transport foundations and tractable deterministic equivalents
◆ 𝘝𝘦𝘤𝘵𝘰𝘳-𝘕𝘰𝘳𝘮𝘦𝘥 𝘋𝘙𝘖: 𝘛𝘩𝘦𝘰𝘳𝘺, 𝘙𝘦𝘧𝘰𝘳𝘮𝘶𝘭𝘢𝘵𝘪𝘰𝘯𝘴, 𝘢𝘯𝘥 𝘗𝘳𝘢𝘤𝘵𝘪𝘤𝘢𝘭 𝘔𝘰𝘥𝘦𝘭𝘪𝘯𝘨
ℓₚ-distance ambiguity sets and norm-based robustness
◆A𝘱𝘱𝘭𝘪𝘤𝘢𝘵𝘪𝘰𝘯𝘴 𝘰𝘧 𝘋𝘙𝘖 𝘪𝘯 𝘐𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘋𝘦𝘤𝘪𝘴𝘪𝘰𝘯 𝘖𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘗𝘳𝘰𝘣𝘭𝘦𝘮𝘴 (𝘋𝘖𝘗𝘴) 𝘶𝘯𝘥𝘦𝘳 𝘜𝘯𝘤𝘦𝘳𝘵𝘢𝘪𝘯𝘵𝘺
Network Design & Facility location, production planning, and capacity expansion
◆ 𝘐𝘮𝘱𝘭𝘦𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘋𝘙𝘖 𝘔𝘰𝘥𝘦𝘭𝘴 𝘪𝘯 𝘗𝘺𝘵𝘩𝘰𝘯 (𝘷𝘪𝘢 𝘎𝘶𝘳𝘰𝘣𝘪)
End-to-end modeling, numerical experiments, and performance evaluation
◆ 𝘋𝘦𝘤𝘰𝘮𝘱𝘰𝘴𝘪𝘵𝘪𝘰𝘯-𝘉𝘢𝘴𝘦𝘥 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯 𝘈𝘭𝘨𝘰𝘳𝘪𝘵𝘩𝘮𝘴 𝘧𝘰𝘳 𝘋𝘙𝘖
Column-and-Constraint Generation (C&CG), iterative refinement, and scalability analysis


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