Data-driven optimization model: Digikala case study
عنوان مقاله: Data-driven optimization model: Digikala case study
شناسه ملی مقاله: IIEC18_058
منتشر شده در هجدهمین کنفرانس بین المللی مهندسی صنایع در سال 1400
شناسه ملی مقاله: IIEC18_058
منتشر شده در هجدهمین کنفرانس بین المللی مهندسی صنایع در سال 1400
مشخصات نویسندگان مقاله:
s Hamidi - Department of Industrial Engineering, Amirkabir University of Technology, Tehran ۱۵۹۱۶۳۴۳۱۱, Iran
s.m.t fatemi ghomia - Department of Industrial Engineering, Amirkabir University of Technology, Tehran ۱۵۹۱۶۳۴۳۱۱, Iran
خلاصه مقاله:
s Hamidi - Department of Industrial Engineering, Amirkabir University of Technology, Tehran ۱۵۹۱۶۳۴۳۱۱, Iran
s.m.t fatemi ghomia - Department of Industrial Engineering, Amirkabir University of Technology, Tehran ۱۵۹۱۶۳۴۳۱۱, Iran
Increasing software as a service (SaaS) requires the provision of more updated models for services,so trying to develop a model customized for the customer is important. We used the linear Knapsack problem model proposed by Mike Hewitt and Emma Frejinger in ۲۰۲۰. Then historical data of Digikala was applied and shown that how the model works on it.
کلمات کلیدی: Optimization modeling, Statistical learning, Mixed integer linear programming, Thirdparty logistics
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1354240/