A Comparison between Chemical Reaction Optimization and Genetic Algorithms for Max Flow Problem Article Swipe
Yasser Mohammad
,
Ola M.
,
Ahmad Sharieh
,
Azzam Sleit
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.14569/ijacsa.2017.080802
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.14569/ijacsa.2017.080802
This paper presents a comparison between the performance of Chemical Reaction Optimization algorithm and Genetic algorithm in solving maximum flow problem with the performance of Ford-Fulkerson algorithm in that. The algorithms have been implemented sequentially using JAVA programming language, and executed to find maximum flow problem using different network size. Ford-Fulkerson algorithm which is based on the idea of finding augmenting path is the most popular algorithm used to find maximum flow value but its time complexity is high. The main aim of this study is to determine which algorithm will give results closer to the Ford-Fulkerson results in less time and with the same degree of accuracy. The results showed that both algorithms can solve Max Flow problem with accuracy results close to Ford Fulkerson results, with a better performance achieved when using the genetic algorithm in term of time and accuracy.
Related Topics
Concepts
Computer science
Algorithm
Maximum flow problem
Java Programming Language
Minimum-cost flow problem
Genetic algorithm
Path (computing)
Out-of-kilter algorithm
Flow network
Java
Mathematical optimization
Shortest path problem
Dijkstra's algorithm
Theoretical computer science
Machine learning
Mathematics
Graph
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.14569/ijacsa.2017.080802
- http://thesai.org/Downloads/Volume8No8/Paper_2-A_Comparison_between_Chemical_Reaction_Optimization.pdf
- OA Status
- hybrid
- Cited By
- 3
- References
- 16
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2752547553
All OpenAlex metadata
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https://openalex.org/W2752547553Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.14569/ijacsa.2017.080802Digital Object Identifier
- Title
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A Comparison between Chemical Reaction Optimization and Genetic Algorithms for Max Flow ProblemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2017Year of publication
- Publication date
-
2017-01-01Full publication date if available
- Authors
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Yasser Mohammad, Ola M., Ahmad Sharieh, Azzam SleitList of authors in order
- Landing page
-
https://doi.org/10.14569/ijacsa.2017.080802Publisher landing page
- PDF URL
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https://thesai.org/Downloads/Volume8No8/Paper_2-A_Comparison_between_Chemical_Reaction_Optimization.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://thesai.org/Downloads/Volume8No8/Paper_2-A_Comparison_between_Chemical_Reaction_Optimization.pdfDirect OA link when available
- Concepts
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Computer science, Algorithm, Maximum flow problem, Java Programming Language, Minimum-cost flow problem, Genetic algorithm, Path (computing), Out-of-kilter algorithm, Flow network, Java, Mathematical optimization, Shortest path problem, Dijkstra's algorithm, Theoretical computer science, Machine learning, Mathematics, Graph, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
-
2021: 1, 2020: 1, 2019: 1Per-year citation counts (last 5 years)
- References (count)
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16Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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