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Liverpool John Moores University

Scheduling of flexible manufacturing systems integrating petri nets and artificial intelligence methods.

Abstract

dc:description.abstract

The work undertaken in this thesis is about the integration of two well-known methodologies: Petri net (PN) model Ii ng/analysis of industrial production processes and Artificial Intelligence (AI) optimisation search techniques. The objective of this integration is to demonstrate its potential in solving a difficult and widely studied problem, the scheduling of Flexible Manufacturing Systems (FIVIS). This work builds on existing results that clearly show the convenience of PNs as a modelling tool for FIVIS. It addresses the problem of the integration of PN and Al based search methods. Whilst this is recognised as a potentially important approach to the scheduling of FIVIS there is a lack of any clear evidence that practical systems might be built. This thesis presents a novel scheduling methodology that takes forward the current state of the art in the area by: Firstly presenting a novel modelling procedure based on a new class of PN (cb-NETS) and a language to define the essential features of basic FIVIS, demonstrating that the inclusion of high level FIVIS constraints is straight forward. Secondly, we demonstrate that PN analysis is useful in reducing search complexity and presents two main results: a novel heuristic function based on PN analysis that is more efficient than existing methods and a novel reachability scheme that avoids futile exploration of candidate schedules. Thirdly a novel scheduling algorithm that overcomes the efficiency drawbacks of previous algorithms is presented. This algorithm satisfactorily overcomes the complexity issue while achieving very promising results in terms of optimality. Finally, this thesis presents a novel hybrid scheduler that demonstrates the convenience of the use of PN as a representation paradigm to support hybridisation between traditional OR methods, Al systematic search and stochastic optimisation algorithms. Initial results show that the approach is promising.

Degree

thesis:*
Name dc:type.qualificationname
phd
Level dc:type.qualificationlevel
doctoral
Grantor dc:publisher.institution
Liverpool John Moores University
Year dc:date.issued
2000

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Reyes Moro, A

Subjects

dc:subject × 3

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:researchonline.ljmu.ac.uk:5527

Chain of custody

source
Harvested from
Liverpool Jon Moores University
Base URL
researchonline.ljmu.ac.uk/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Reyes Moro, A. Scheduling of flexible manufacturing systems integrating petri nets and artificial intelligence methods.. doctoral thesis, Liverpool John Moores University, 2000. https://doi.org/10.24377/LJMU.t.00005527