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A Decentralized Approach to Solve Group AHP with Agreements by Consensus

  • Miguel RebolloEmail author
  • Alberto Palomares
  • Carlos Carrascosa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10207)

Abstract

The analytical hierarchical process (AHP) is a multi-criteria, decision-making process that has demonstrated to be of a high utility to achieve complex decisions. This work presents a method to apply it in grupal decisions, where the weights that each user assigns to the criteria are different and private. A combination of consensus process and gradient ascent is used to reach a common agreement that optimizes the utility of the decision using the information exchanged in the local neighborhood exclusively.

The AHP problem is modeled through a multilayer network. Each one of the criteria are negotiated by consensus with the direct neighbors on each layer of the network. Furthermore, each node performs a transversal gradient ascent and corrects locally the deviations from the personal decision to keep the best option.

The process locates the global optimal decision, taking into account that this global function is never calculated nor known by any of the participants. If there is not a global optimal decision where all the participants have a not null utility, but a set of suboptimal decisions, they are automatically divided into different groups that converges into these suboptimal decisions.

Keywords

Complex networks Consensus Gradient descent Analytical hierarchical process Agreement 

Notes

Acknowledgements

This work is supported by the PROMETEOII/2013/019 and TIN2015-65515-C4-1-R projects of the spanish government.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Miguel Rebollo
    • 1
    Email author
  • Alberto Palomares
    • 1
  • Carlos Carrascosa
    • 1
  1. 1.Universitat Politècnica de ValènciaValenciaSpain

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