Rescheduling of unrelated parallel machines with job-dependent setup times under forecasted machine breakdown

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We address a rescheduling problem of unrelated parallel machines with job-dependent setup times where a machine breakdown is known in advance. Typical rescheduling methods usually re-assign or re-sequence jobs from a given schedule after machines break down. Recently, machine breakdowns can be forecasted with high accuracy before their actual occurrences from IoT sensors or artificial intelligence methods. We therefore define a new rescheduling problem in which jobs are re-assigned before machine breakdowns occur, and propose a mathematical programming model with three objective measures, makespan, stability and penalty cost. We then develop a simulated annealing (SA) algorithm combined with a fuzzy logic controller for adjusting the parameters in SA. We demonstrate the performance of the proposed algorithm with extensive experiments.
Publisher
TAYLOR & FRANCIS LTD
Issue Date
2021-09
Language
English
Article Type
Article
Citation

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, v.59, no.17, pp.5236 - 5258

ISSN
0020-7543
DOI
10.1080/00207543.2020.1775910
URI
http://hdl.handle.net/10203/287552
Appears in Collection
IE-Journal Papers(저널논문)
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