Coordinating patient preferences through automated negotiation: A multiagent systems model for diagnostic services scheduling

Jie Gao, Terrence Wong, Chun Wang*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

Abstract

This paper presents a multiagent systems model for patient diagnostic services scheduling. We assume a decentralized environment in which patients are modeled as self-interested agents who behave strategically to advance their own benefits rather than the system wide performance. The objective is to improve the utilization of diagnostic imaging resources by coordinating patient individual preferences through automated negotiation. The negotiation process consists of two stages, namely patient selection and preference scheduling. The contract-net protocol and simulated annealing based meta-heuristics are used to design negotiation protocols at the two stages respectively. In terms of game theoretic properties, we show that the proposed protocols are individually rational and incentive compatible. The performance of the preference scheduling protocol is evaluated by a computational study. The average percentage gap analysis of various configurations of the protocol shows that the results obtained from the protocol are close to the optimal ones. In addition, we present the algorithmic properties of the preference scheduling protocol through the validation of a set of eight hypotheses.

Original languageEnglish
Article number100934
Number of pages13
JournalAdvanced Engineering Informatics
Volume42
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • Appointment scheduling
  • Automated negotiation protocol
  • Diagnostic service scheduling
  • Meta-heuristic
  • Multiagent systems
  • Patient preference

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