New algorithms exploiting randomness in lead times in inventory systems

Taneja, Aditi

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https://hdl.handle.net/2142/120578 Copy

Description

Title

New algorithms exploiting randomness in lead times in inventory systems

Author(s)

Taneja, Aditi

Issue Date

2023-05-04

Director of Research (if dissertation) or Advisor (if thesis)

• Stolyar, Aleksandr
• Wang, Qiong

Department of Study

Industrial&Enterprise Sys Eng

Discipline

Industrial Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• GBS
• Pipeline
• CBS
• Adaptive

Abstract

In this work, we examine a traditional single-item inventory system where unfilled demands result in backlog. The time it takes to restock varies at random and is independent and identically distributed, leading to orders crossing paths.The research conducted by (1) demonstrates that the randomness of lead times in inventory systems can potentially result in infinite improvements compared to constant lead times. The aim of this project is to investigate the feasibility of achieving such improvements while considering practical system constraints and identifying policies that are both effective and practical. This study introduces two new policies, Adaptive and Pipeline, in addition to the discrete-time version of the Generalized Base Stock policy introduced in (1) and Constant Base Stock Policy ((2)). The performance of the four policies are evaluated through simulations, with a focus on the impact of lead time distributions. The results indicate that the proposed policies can lead to significant performance improvements under practical constraints, with larger improvements observed when lead time variability is higher. We find that the Pipeline policy is found to be the most effective and practical for implementation.

Graduation Semester

2023-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/120578

Copyright and License Information

Copyright 2023 Aditi Taneja

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