Collaborative distributed decision making for large scale disaster relief operations: Drawing analogies from robust natural systems

Roberto G. Aldunate, Feniosky Pena-Mora, Gene E. Robinson

Research output: Contribution to journalArticlepeer-review

Abstract

One of the most ignored, but urgent and vital challenges confronting society today is the vulnerability of urban areas to extreme events. Current organization of response systems, predominantly based on a command and control model, limits their effectiveness and efficiency. Particularly, in decision-making processes where a large number of actors may be involved. In this article, a new distributed collaborative decision-making model is proposed to overcome command and control limitations encountered in stressful, hostile, chaotic, and large-scale settings. This model was derived by borrowing concepts from the collective decision making of honeybees foraging, a successful process in solving complex tasks within complex settings. The model introduced in this article was evaluated through differential equations, i.e., continuous analysis, and difference equations, i.e., discrete analysis. The most important result found is that the best available option in any large-scale decision-making problem can be configured as an attractor, in a distributed and timely manner. We suggest that the proposed model has the potential to facilitate decision-making processes in large-scale settings.

Original languageEnglish (US)
Pages (from-to)28-38
Number of pages11
JournalComplexity
Volume11
Issue number2
DOIs
StatePublished - Jan 1 2005

Keywords

  • Complex systems
  • Distributed convergence
  • Distributed decision making
  • Robust natural systems

ASJC Scopus subject areas

  • General

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