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Optimizing Opponents Selection in Bilateral Contracts Negotiation with Particle Swarm

  • Francisco Silva
  • Ricardo Faia
  • Tiago PintoEmail author
  • Isabel Praça
  • Zita Vale
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 887)

Abstract

This paper proposes a model based on particle swarm optimization to aid electricity markets players in the selection of the best player(s) to trade with, to maximize their bilateral contracts outcome. This approach is integrated in a Decision Support System (DSS) for the pre-negotiation of bilateral contracts, which provides a missing feature in the state-of-art, the possible opponents analysis. The DSS determines the best action of all the actions that the supported player can take, by applying a game theory approach. However, the analysis of all actions can easily become very time-consuming in large negotiation scenarios. The proposed approach aims to provide the DSS with an alternative method with the capability of reducing the execution time while keeping the results quality as much as possible. Both approaches are tested in a realistic case study where the supported player could take almost half a million different actions. The results show that the proposed methodology is able to provide optimal and near-optimal solutions with an huge execution time reduction.

Keywords

Automated negotiation Bilateral contracts Decision Support System Electricity Markets Game theory Particle Swarm Optimization 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Francisco Silva
    • 1
  • Ricardo Faia
    • 1
  • Tiago Pinto
    • 1
    • 2
    Email author
  • Isabel Praça
    • 1
  • Zita Vale
    • 1
  1. 1.GECAD - Knowledge Engineering and Decision Support Research CenterInstitute of Engineering – Politechnic of Porto (ISEP/IPP)PortoPortugal
  2. 2.BISITE – Research CentreUniversity of SalamancaSalamancaSpain

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