An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production

Even though research in flow shop production scheduling has been carried out for many decades, there is still a gap between research and applicationespecially in manufacturing paradigms such as one-of-a-kind production (OKP) that intensely challenges real time adaptive production scheduling and cont...

Full description

Bibliographic Details
Main Authors: Li, Wei, Nault, B., Xue, D., Tu, Y.
Format: Conference Paper
Published: 2011
Online Access:http://hdl.handle.net/20.500.11937/39811
_version_ 1848755694993408000
author Li, Wei
Nault, B.
Xue, D.
Tu, Y.
author_facet Li, Wei
Nault, B.
Xue, D.
Tu, Y.
author_sort Li, Wei
building Curtin Institutional Repository
collection Online Access
description Even though research in flow shop production scheduling has been carried out for many decades, there is still a gap between research and applicationespecially in manufacturing paradigms such as one-of-a-kind production (OKP) that intensely challenges real time adaptive production scheduling and control. Indeed, many of the most popular heuristics continue to use Johnson's algorithm (1954) as their core. This paper presents a state space (SS) heuristic, integrated with a closed-loop feedback control structure, to achieve adaptive production scheduling and control in OKP. Our SS heuristic, because of its simplicity and computational efficiency, has the potential to become a core heuristic. Through a series of case studies, including an industrial implementation in OKP, our SS-based production scheduling and control system demonstrates significant potential to improve production efficiency. © 2010 Elsevier Ltd. All rights reserved.
first_indexed 2025-11-14T09:00:23Z
format Conference Paper
id curtin-20.500.11937-39811
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:00:23Z
publishDate 2011
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-398112018-03-29T09:07:45Z An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production Li, Wei Nault, B. Xue, D. Tu, Y. Even though research in flow shop production scheduling has been carried out for many decades, there is still a gap between research and applicationespecially in manufacturing paradigms such as one-of-a-kind production (OKP) that intensely challenges real time adaptive production scheduling and control. Indeed, many of the most popular heuristics continue to use Johnson's algorithm (1954) as their core. This paper presents a state space (SS) heuristic, integrated with a closed-loop feedback control structure, to achieve adaptive production scheduling and control in OKP. Our SS heuristic, because of its simplicity and computational efficiency, has the potential to become a core heuristic. Through a series of case studies, including an industrial implementation in OKP, our SS-based production scheduling and control system demonstrates significant potential to improve production efficiency. © 2010 Elsevier Ltd. All rights reserved. 2011 Conference Paper http://hdl.handle.net/20.500.11937/39811 10.1016/j.cor.2010.05.002 restricted
spellingShingle Li, Wei
Nault, B.
Xue, D.
Tu, Y.
An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
title An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
title_full An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
title_fullStr An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
title_full_unstemmed An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
title_short An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
title_sort efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
url http://hdl.handle.net/20.500.11937/39811