We focus on the spare parts inventory control under demand uncertainty, particularly during the New Product Introduction (NPI) phase when historical data is limited. Most conventional spare parts inventory control models assume demand follows a Poisson process with a known rate. However, the rate may not be known when limited data is available. We propose an adaptive robust optimization (ARO) approach to multi-item spare parts inventory control. We show how the ARO problem can be reformulated as a tractable deterministic integer programming problem. We develop an efficient algorithm to obtain near-optimal solutions for thousands of items. We demonstrate the practical value of our model through a case study at ASML, a leading semiconductor equipment supplier. The case study reveals that our model consistently achieves higher service levels at lower costs than the conventional stochastic optimization approach employed at ASML.
Ahmadreza Marandi: Robust Spare Parts Inventory Management 6 February 2025 16:00 - 17:00
About Ahmadreza Marandi: Robust Spare Parts Inventory Management
Starting date
- 6 February 2025
Time
- 16:00 - 17:00
Location
- VU Main Building
Address
- De Boelelaan 1105
- 1081 HV Amsterdam
Organised by
- Operations Analytics
Language
- English
Ahmadreza Marandi
Ahmadreza Marandi is an assistant professor at both the Department of Industrial Engineering and Innovation Sciences and the Eindhoven Artificial Intelligence Systems Institute at Eindhoven University of Technology. He is an expert in Robust Optimization. His research focuses on leveraging available data to make robust and resilient medium- to long-term decisions and designing algorithms to handle uncertainty. His practical research interests lie primarily in supply chain management and high-tech industries. Ahmadreza is also a member of the Scientific Steering Group of the Resilience Engineering Center at 4TU, co-organizes the renowned "Robust Optimization Webinars" series, and one of the co-chairs of the optimization flagship conference, ISMP2027.
Interested in attending the seminar or in giving a talk?
Please send an email to Tim Oosterwijk