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Permutation Flow-shop : Taillard and VFR benchmarks best known solutions (updated according to linked report)

Authors: Brunner, Olivier;

Permutation Flow-shop : Taillard and VFR benchmarks best known solutions (updated according to linked report)

Abstract

This dataset completes the report of the same author (Olivier Brunner) that can be viewed at : https://doi.org/10.5281/zenodo.15696776 It is composed of three consistant CSV files - i.e. with the same columns. The report abstract is : This report presents solutions that, as of the date of publication, improve the cost (makespan) for 50 instances of the Permutation Flow-Shop Problem (PFSP) proposed by Eric Taillard or by Eva Vallada, Rubén Ruiz, and Jose M. Framinan. This report may help those who assess the quality of heuristics based on their ability to approach the best-known solutions. Three algorithmic techniques used are also presented: the super-prohibition sieve excluding paths with weights exceeding a given bound, the adaptive compartmental neighborhood with selective 2-closing, and finally the makespan calculation performed using upper-windowed multi-numbers. The same versioning is used for the report and for the dataset. The dataset was created and starts at version 5 of the report. Sources 100 & 101 : This dataset reflects an ongoing work. Further updates will be posted until every open instance has been tested. Source 0 : This dataset is based on the best known solutions sumerized and uploaded by Jan Gmys in feb, 2021. It can be viewed at : https://doi.org/10.5281/zenodo.4542886 Source 50 : It also includes the solutions uploaded by J. A. Alejandro-Soto in july, 2025. It can be viewed at : https://doi.org/10.5281/zenodo.15832204

Keywords

Flow-Shop, Permutation Flowshop, Flow shop, Permutation Flow-Shop, Permutation flow shop, Flowshop

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average