A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling
The multiprocessor task scheduling problem has received considerable attention over the last three decades. In this context, a wide range of studies focuses on the design of evolutionary algorithms. These papers deal with many topics, such as task characteristics, environmental heterogeneity, and op...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/8/2/26 |
| _version_ | 1827719002840891392 |
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| author | Eduardo C. da Silva Paulo H. R. Gabriel |
| author_facet | Eduardo C. da Silva Paulo H. R. Gabriel |
| author_sort | Eduardo C. da Silva |
| collection | DOAJ |
| description | The multiprocessor task scheduling problem has received considerable attention over the last three decades. In this context, a wide range of studies focuses on the design of evolutionary algorithms. These papers deal with many topics, such as task characteristics, environmental heterogeneity, and optimization criteria. To classify the academic production in this research field, we present here a systematic literature review for the directed acyclic graph (DAG) scheduling, that is, when tasks are modeled through a directed acyclic graph. Based on the survey of 56 works, we provide a panorama about the last 30 years of research in this field. From the analyzes of the selected studies, we found a diversity of application domains and mapped their main contributions. |
| first_indexed | 2024-03-10T20:34:27Z |
| format | Article |
| id | doaj.art-f9833c5cdeb54b14a9108b0aea06c979 |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-10T20:34:27Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-f9833c5cdeb54b14a9108b0aea06c9792023-11-19T21:11:36ZengMDPI AGComputation2079-31972020-04-01822610.3390/computation8020026A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG SchedulingEduardo C. da Silva0Paulo H. R. Gabriel1Faculty of Computer Science, Federal University of Uberlândia, Uberlândia, MG 38408-100, BrazilFaculty of Computer Science, Federal University of Uberlândia, Uberlândia, MG 38408-100, BrazilThe multiprocessor task scheduling problem has received considerable attention over the last three decades. In this context, a wide range of studies focuses on the design of evolutionary algorithms. These papers deal with many topics, such as task characteristics, environmental heterogeneity, and optimization criteria. To classify the academic production in this research field, we present here a systematic literature review for the directed acyclic graph (DAG) scheduling, that is, when tasks are modeled through a directed acyclic graph. Based on the survey of 56 works, we provide a panorama about the last 30 years of research in this field. From the analyzes of the selected studies, we found a diversity of application domains and mapped their main contributions.https://www.mdpi.com/2079-3197/8/2/26DAG schedulingevolutionary algorithmssystematic literature reviewcomputational environmentoptimization criteria |
| spellingShingle | Eduardo C. da Silva Paulo H. R. Gabriel A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling Computation DAG scheduling evolutionary algorithms systematic literature review computational environment optimization criteria |
| title | A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling |
| title_full | A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling |
| title_fullStr | A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling |
| title_full_unstemmed | A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling |
| title_short | A Comprehensive Review of Evolutionary Algorithms for Multiprocessor DAG Scheduling |
| title_sort | comprehensive review of evolutionary algorithms for multiprocessor dag scheduling |
| topic | DAG scheduling evolutionary algorithms systematic literature review computational environment optimization criteria |
| url | https://www.mdpi.com/2079-3197/8/2/26 |
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