Thesis Defense - Furkan Kasapoğlu (MSDS)

Furkan Kasapoğlu – M.Sc. Data Science

Assoc. Prof. Okan Örsan Özener – Advisor

Date: 25.05.2022

Time: 13:30

Location:  AB1 232

ALLOCATING COSTS IN A LOT SIZING GAME USING NOVEL MACHINE LEARNING METHODS

Thesis Committee:

Assoc. Prof. Okan Örsan Özener, Özyeğin University

Asst.  Prof.  Başak Altan Özener, Özyeğin University

Assoc. Prof.  Uğur Çelikyurt, Koç University

Abstract:

In supply chain management (SCM), effective resource utilization is the key to achieving certain strategic benefits such as minimizing costs, increasing service levels, reducing inventories, increasing responsiveness, and finally improving customer satisfaction. Collaborative approaches among supply chain entities have become increasingly popular to increase resource utilization. In this thesis, we analyze a collaborative production setting where several companies facing varying demands throughout a finite planning horizon attempt to reduce their procurement costs by ordering from a common supplier. As the capacity of the common supplier is better utilized in such a collaborative solution, it will yield benefits that will be shared by the collaborators. Our objective is to design a cost allocation framework to ensure the sustainability of the collaborative purchasing organization. We propose various methods, including novel and computationally efficient machine learning based methods, using two different architectures, gradient boosting mechanism, and artificial neural networks which ensure the scalability of the proposed framework. We perform an extensive computational study and observe that our proposed method significantly outperforms the generic methods in the literature in terms of solution quality and computation time.

Bio: 

Furkan Kasapoğlu graduated from Bornova Anatolian High School in 2012. He received his bachelor’s degree in Economics from Boğaziçi University in 2017. Since his graduation, he has been working for four years in ING as Data Scientist. He joined the Master of Science program in Data Science at Özyeğin University in 2020. Currently, Furkan is working as Data Scientist in Afiniti for more than a year. His research focuses on machine learning and deep learning.