Towards pre-emptive resilience in military supply chains: A compromise decision support model-based approach

Sani Mohammed, Shehu; Schaefer, Dirk; Milisavljevic-Syed, Jelena

Abstract

The complex and dynamic nature of military supply chains (MSC) requires constant vigilance to sense potential vulnerabilities. Several studies have employed decision support models for the optimization of their operations. These models are often limited to a best single-point solution unsuitable for complex MSC constellations. In this article, the authors present a novel approach based on decision support models to explore a range of satisficing solutions against disruptions in MSCs using a compromise Decision Support Problem (cDSP) construct and Decision Support in the Design of Engineered Systems (DSIDES). Two cases were evaluated: (1) a baseline scenario with no disruption and (2) with disruption to achieve target values of three goals: (1) minimizing lead time, (2) maximizing demand fulfilment and (3) maximizing vehicle utilization. The results obtained in Case 1 identified a more stable solution space with minimal deviations from the target value, while in Case 2 the solution space was unstable with deviations from the target values.

Citation

Sani Mohammed, S., Schaefer, D., & Milisavljevic-Syed, J. (2023). Towards pre-emptive resilience in military supply chains: A compromise decision support model-based approach. Production and Manufacturing Research, 11(1), Article 2220768. https://doi.org/10.1080/21693277.2023.2220768

• Journal Article Type: Article
• Acceptance Date: May 29, 2023
• Online Publication Date: Jun 9, 2023
• Publication Date: Jan 1, 2023
• Deposit Date: Apr 3, 2024
• Publicly Available Date: Apr 3, 2024
• Journal: Production and Manufacturing Research
• Electronic ISSN: 2169-3277
• Publisher: Taylor and Francis Group
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 1
• Article Number: 2220768
• DOI: https://doi.org/10.1080/21693277.2023.2220768
• Keywords: Resilience; Disruptions; Decision support; Military supply chain; Solution space exploration
• Public URL: https://hull-repository.worktribe.com/output/4618545