Title of article :
Data-driven optimization model: Digikala case study
Author/Authors :
Hamidi, Sanaz Department of Industrial Engineering - Amirkabir University of Technology, Tehran, Iran , Fatemi Ghomi, Mohammad Taghi Department of Industrial Engineering - Amirkabir University of Technology, Tehran, Iran
Abstract :
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 2020. Then historical data
of Digikala was applied and shown that how the model works on it.
Keywords :
Optimization modeling , statistical learning , mixed integer linear programming , third-party logistics
Journal title :
Journal of Industrial and Systems Engineering (JISE)
