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Priority-based scheduling in flexible system using AIS with FLC approach

Chan, Felix T.S.; Prakash, Anuj; Mishra, Nishikant

Authors

Felix T.S. Chan

Anuj Prakash



Abstract

In the present paper, an extensive decision-making problem of scheduling in flexible environment has been discussed. The novelty of the research is to allocate the machines to the operations on the basis of the priority. The highly prioritised machines are allocated first but least prioritised machines are also allocated for on-time delivery. The priority-based schedule provides a tradeoff approach between the utilisation and lead time. The problem has been tested on make-span as performance measure along with the sum of priority of all selected machines. To unravel the complexities of this problem, a heuristic based on a new approach, called artificial immune system (AIS) has been proposed. To strengthen AIS, a fuzzy logic controller (FLC) has been incorporated in the AIS heuristic. FLC changes the hypermutation rate adaptively at iteration. A numerical example has been taken for showing the efficacy of the proposed algorithm. The supremacy of the problem has been shown by the randomly generated data-set with increased complicacy of the problems. The results are also validated by statistical analysis using analysis of variance. © 2013 Taylor and Francis Group, LLC.

Citation

Chan, F. T., Prakash, A., & Mishra, N. (2013). Priority-based scheduling in flexible system using AIS with FLC approach. International Journal of Production Research, 51(16), 4880-4895. https://doi.org/10.1080/00207543.2013.774500

Journal Article Type Article
Acceptance Date Jan 27, 2013
Online Publication Date May 8, 2013
Publication Date Aug 1, 2013
Deposit Date Jun 8, 2022
Journal International Journal of Production Research
Print ISSN 0020-7543
Electronic ISSN 1366-588X
Publisher Taylor and Francis
Peer Reviewed Peer Reviewed
Volume 51
Issue 16
Pages 4880-4895
DOI https://doi.org/10.1080/00207543.2013.774500
Keywords Scheduling; Make-span; Artificial immune system; Fuzzy logic controller
Public URL https://hull-repository.worktribe.com/output/3613986