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Cited by 342

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Flowshop-scheduling problems with makespan criterion: a review

Reza Hejazi *, S., Saghafian, S.·2005·International Journal of Production Research

Abstract

This paper is a complete survey of flowshop-scheduling problems and contributions from early works of Johnson of to recent approaches of metaheuristics of 2004. It mainly considers a flowshop problem with a makespan criterion and it surveys some exact methods (for small size problems), constructive heuristics and developed improving metaheuristic and evolutionary approaches as well as some well-known properties and rules for this problem. Each part has a brief literature review of the contributions and a glimpse of that approach before discussing the implementation for a flowshop problem. Moreover, in the first section, a complete literature review of flowshop-related scheduling problems with different assumptions as well as contributions in solving these other aspects is considered. This paper can be seen as a reference to past contributions (particularly in n/m/p/c max or equivalently F/prmu/c max) for future research needs of improving and developing better approaches to flowshop-related scheduling problems.

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Metadata

Authors
Reza Hejazi *, S., & Saghafian, S.
Venue
International Journal of Production Research
Published
2005-07-15
Volume
43
Issue
14
Pages
2895-2929
ISSN
  • 0020-7543 (ISSN-L)
  • 1366-588X
OpenAlex
W2001664299
Cited by
342
References
39
FWCI
28.56
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Flowshop-scheduling problems with makespan criterion: a review. https://app.cochat.ai/papers/10.1080/0020754050056417
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Reza Hejazi *, S., & Saghafian, S. (2005). Flowshop-scheduling problems with makespan criterion: a review. International Journal of Production Research. https://doi.org/10.1080/0020754050056417

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.