A neural network model for the free-ranging AGV route-planning problem

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)217-227
Journal / PublicationJournal of Intelligent Manufacturing
Volume7
Issue number3
Publication statusPublished - 1996

Abstract

This paper describes the development of a prototype neural network model for the free-ranging AGV route-planning problem. The vehicle planner operates in quasi-real time. A small planning horizon is set and all transport requests existing at the beginning of a planning horizon are examined. A neural network model is proposed to perform dispatching and routing tasks for the AGVs. Its goal is to satisfy the transport requests in the shortest time and in a non-conflicting manner, subject to the global manufacturing objective of maximizing throughputs. Based on Kohonen's self-organizing feature maps, we develop three efficient planning algorithms for the single and multiple AGV problems. The simulation results indicate that the proposed neural network approach gives very efficient solutions. © 1996 Chapman & Hall.

Research Area(s)

  • AGV, Kohonen's self-organizing network, Route planning and dispatching

Citation Format(s)

A neural network model for the free-ranging AGV route-planning problem. / Hao, Gang; Shang, Jen S.; Vargas, Luis G.

In: Journal of Intelligent Manufacturing, Vol. 7, No. 3, 1996, p. 217-227.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review