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Area of Science:

  • Systems Engineering
  • Decision Science
  • Operations Research

Background:

  • Complex systems require effective recovery, adaptation, and reorganization post-disruption.
  • Existing resilience evaluation methods often use single performance measures, which is insufficient for multifaceted systems.
  • Multiple, noncommensurate performance measures are necessary for accurately assessing complex system resilience.

Purpose of the Study:

  • To present a novel framework for modeling resilience in complex systems with competing performance measures.
  • To develop a model for decision-making regarding investments in complex systems, incorporating diverse stakeholder perspectives.
  • To provide a practical approach for evaluating and enhancing system resilience.

Main Methods:

  • Development of a resilience modeling framework for complex systems.
  • Application of multicriteria decision analysis (MCDA) to incorporate multiple stakeholder perspectives.
  • Demonstration of the framework using a real-world case study.

Main Results:

  • The proposed framework effectively models resilience considering competing performance measures.
  • The decision-making model successfully integrates multiple stakeholder viewpoints for investment analysis.
  • The case study validates the framework's applicability to real-world complex systems.

Conclusions:

  • The developed framework offers a comprehensive approach to understanding and managing system resilience.
  • This methodology supports informed investment decisions in complex systems like supply chains and infrastructure.
  • Enhanced resilience assessment is crucial for the stability and adaptability of modern complex systems.