Resilient supply chain network design under super-disruption considering inter-arrival time dependency: A new data-driven stochastic optimization approach

Vali-Siar, Mohammad Mahdi, Tikani, Hamid, Demir, Emrah ORCID: https://orcid.org/0000-0002-4726-2556 and Shamstabar, Yousof 2026. Resilient supply chain network design under super-disruption considering inter-arrival time dependency: A new data-driven stochastic optimization approach. Transportation Research Part E: Logistics and Transportation Review Item availability restricted.

	PDF - Accepted Post-Print Version Restricted to Repository staff only Available under License Creative Commons Attribution. Download (3MB)
	PDF (Provisional file) - Accepted Post-Print Version Download (17kB)

Abstract

During large-scale disruptions, particularly super-disruptions such as global pandemics or large-scale natural disasters, supply chains are exposed to significant adverse impacts. This paper addresses the resilience in a supply chain network design problem under disruption risk by explicitly modeling the dependency between the inter-arrival times of disruptive events and severity of their consequences. A novel data-driven stochastic optimization framework is proposed to consider the ripple effects that typically propagate across supply chain networks following severe disruptions. Specifically, we have devised a hybrid methodology incorporating a clustering algorithm as an unsupervised machine learning technique, a phase-type disruption model, and a two- stage stochastic model. To elaborate, a genetic-based clustering algorithm is used to identify the structure of the mentioned dependencies of the input data. Subsequently, we leverage phase-type distributions and associated theorems to ascertain the probability distributions of disruptions. A novel mathematical model is developed to design the supply chain using the scenarios generated based on the obtained distributions, which is then solved using the Lagrangian decomposition method and a new hyper-matheuristic algorithm. The computational efficiency and practical value of the proposed approach are illustrated through a real-world case study. The findings demonstrate the effectiveness of developed methodology in designing a resilient supply chain. Moreover, the proposed resilience strategies can substantially improve the supply chain objective, compared to the non-resilient approach.

Item Type:	Article
Status:	In Press
Schools:	Schools > Business (Including Economics)
Publisher:	Elsevier
ISSN:	1366-5545
Date of First Compliant Deposit:	18 December 2025
Date of Acceptance:	15 December 2025
Last Modified:	19 Dec 2025 09:30
URI:	https://orca.cardiff.ac.uk/id/eprint/183358

Actions (repository staff only)

Edit Item