Algorithm metrics results and engineering application data underlying the publication: Many-objective Optimization of Energy-Efficient Hybrid Flow-shop Scheduling Based on Positive Projection Grey Target Mechanism (dataset)

Algorithm metrics results and engineering application data underlying the publication: Many-objective Optimization of Energy-Efficient Hybrid Flow-shop Scheduling Based on Positive Projection Grey Target Mechanism

doi: 10.4121/19681959.v1

Datacite citation style:

zhang, zheng; Zhu, Guang-Yu (2022): Algorithm metrics results and engineering application data underlying the publication: Many-objective Optimization of Energy-Efficient Hybrid Flow-shop Scheduling Based on Positive Projection Grey Target Mechanism. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19681959.v1

Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

choose version: version 2 - 2022-08-04 (latest)

version 1 - 2022-04-29

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988

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148

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keywords

energy-efficient, Flow shop scheduling, Multi-Objective Optimization, preventive maintenance

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CC0

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RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Zheng Zhang

, Guang-Yu Zhu

To achieve the goal of carbon-neutral, the energy-efficient scheduling has attracted the attention of many companies and researchers. This data set is the algorithm metrics results and engineering application example data of the paper

"Many-objective Optimization of Energy-Efficient Hybrid Flow-shop Scheduling Based on Positive Projection Grey Target Mechanism". It is for the convenience of readers to better understand the paper.

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