Intelligent combinatorial auctions of decentralized task assignment for AGV with multiple loading capacity

Muhammad Hafidz Fazli bin Md Fauadi, Saifudin Hafiz Yahaya, Tomohiro Murata

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The need to have an effi{ligature}cient transportation system has attracted worldwide attention. Although there is increasing demand to implement distributed control system for industrial applications, there is still an unexplored potential of deploying distributed transportation system. This paper focuses on dynamic assignment of transportation requests to a fl{ligature}eet of vehicles in real time. We introduce an improved combinatorial auction methodology to accommodate the distributed task assignment procedure. Based on a multiagent architecture, each vehicle is represented by an intelligent agent that bids for task and plans its own schedule. On the other hand, the auctioneer has the objective of minimizing transportation tardiness. An automated guided vehicle (AGV) has been selected as the case study, and numerical experiments have been carried out. The result obtained shows that the improved task assignment approach is able to produce performance competitive to a conventional task assignment.

Original languageEnglish
Pages (from-to)371-379
Number of pages9
JournalIEEJ Transactions on Electrical and Electronic Engineering
Volume8
Issue number4
DOIs
Publication statusPublished - 2013 Jul

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Distributed parameter control systems
Intelligent agents
Industrial applications
Experiments

Keywords

  • Automated guided vehicle (AGV)
  • Combinatorial auctions
  • Intelligent agent
  • Multiload AGV

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Intelligent combinatorial auctions of decentralized task assignment for AGV with multiple loading capacity. / Fauadi, Muhammad Hafidz Fazli bin Md; Yahaya, Saifudin Hafiz; Murata, Tomohiro.

In: IEEJ Transactions on Electrical and Electronic Engineering, Vol. 8, No. 4, 07.2013, p. 371-379.

Research output: Contribution to journalArticle

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