Operations Research 2025
Abstract Submission

176. Multi-Stage Aggregate Production Planning from a Lean Resilience Perspective

Invited abstract in session TC-10: Fulfillment Operations II, stream Supply Chain Management and Production.

Thursday, 11:45-13:15
Room: H16

Authors (first author is the speaker)

1. Maximilian Schön
TU Dresden
2. Chenghao Dai
TU Dresden
3. Frank Herrmann
OTH Regensburg
4. Thorsten Claus
IHI Zittau, TU Dresden

Abstract

In today’s increasingly uncertain and dynamic environment, supply chain resilience has become a critical capability for companies to prepare for, respond to, and recover from disruptions. Classically, resilience is known as a driver of costs. Therefore, recent research has established the concept of lean resilience, balancing resilience and efficiency in the sense of a cost-benefit analysis. Traditional ways of dealing with operational fluctuations, like safety stock and capacity, are insufficient to compensate for large-scale disruptions or would, if nonetheless utilized for this purpose, lead to unnecessarily high costs. Therefore, capabilities that are specifically designed to deal with large-scale disruptions need to be incorporated.

In this contribution, a multi-stage aggregate production planning problem is addressed to facilitate resilient planning from a practical perspective in a disruptive context. A multi-objective, stochastic model for aggregate production planning is proposed, integrating both the economical objective and resilience metrics, along with capabilities to compensate for large-scale fluctuations along several dimensions. The probability distribution of the disruption scenarios is derived from an analysis of relevant news collected from the internet. The model is then applied to a realistic case study of a consumer electronics supply chain facing the risk of disruptive events. Lastly, these numerical experiments are utilized to evaluate the results of this application.

Keywords

Status: accepted

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