An agent‐based model for improved system of systems decision making in air transportation. Issue 1 (24th August 2018)

• Record Type: Journal Article
• Authors: Esmaeilzadeh, Ehsan; Grenn, Michael W.; Roberts, Blake
• Is Part Of: Systems engineering. Volume 22:Issue 1(2019)
• Page Start: 20
• Page End: 42
• Publication Date: 2018-08-24
• Subjects: agent‐based simulation -- system design and evaluation -- system of systems; Systems engineering -- Periodicals; 620.0011
• DOI: 10.1002/sys.21465
• Languages: English
• ISSNs: 1098-1241

Abstract

Abstract: Team collaboration and decision making have a significant role in the overall performance of complex system of systems (SoS). Improved systems engineering (SE) processes and tools are needed during the systems development lifecycle to make decisions and rapidly evaluate and assess multiple design alternatives to effectively select architectural design strategies that result in the highest mission performance. Therefore, the early and consistent evaluation of these strategies and collaborative team decisions are essential. The degree of utility of alternative decision strategy designs may vary given the condition, but conditions are not always considered when these decisions are being made. This article applies the SE principles of design for change and flexibility in an agent‐based model for simulation of design alternatives for systems analysis and decision making in evaluating and selecting the decision(s) for SoS comprised of collaborative teams that result in higher mission performance. The authors apply the proposed agent‐based model to test the flight delay within the SoS structure of the air transportation domain. The flight delays are due to the management strategies initiated by the air traffic facilities to balance the air demand and capacity when conditions are not normal (such as severe weather). The experimental results suggest that: (1) the current strategies may result in unnecessary delays and underdelivery of flights to the airport during the hours where demand is well below capacity; (2) aggressive strategies may have the reverse effect; and (3) longer‐duration strategies have a more significant impact on delays during severe weather conditions.