Data-driven optimization model: Digikala case study

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.

Keywords:

Optimization modeling , Statistical learning , Mixed integer linear programming , Thirdparty logistics