An Advanced Ant Colony Algorithm for Constrained Multi-objective Optimization Problem Article Swipe
Yan-mei LUO
,
Guoyan Yu
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.12783/dtcse/msota2018/27589
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.12783/dtcse/msota2018/27589
Most of the existing multi-objective optimization algorithms focused on how to transform the multi-objectives into single objective, while little consideration was given on how to deal with constraint condition. To deal with this problem, an improved ant colony optimization algorithm is proposed in this paper. Logistic chaos is used to initialize the group, which makes the pheromone concentration difference on each path at the initial time, provided direction guidance for ants at the beginning of searching and improved search efficiency. Furthermore, the idea of Pareto sorting is used to sort the feasible solution, and get the Pareto solution set. The numerical experiments show that the proposed algorithm achieves significantly better performance than the others on most of the tested problems, which indicates the superiority of the proposed algorithm for solving constrained multi-objective optimization problems (CMOPs).
Related Topics
Concepts
Ant colony optimization algorithms
Mathematical optimization
Sorting
Pareto principle
sort
Computer science
Path (computing)
Multi-objective optimization
Set (abstract data type)
Algorithm
Optimization problem
Constraint (computer-aided design)
Mathematics
Geometry
Information retrieval
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.12783/dtcse/msota2018/27589
- http://dpi-proceedings.com/index.php/dtcse/article/download/27589/26999
- OA Status
- diamond
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2913070060
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2913070060Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.12783/dtcse/msota2018/27589Digital Object Identifier
- Title
-
An Advanced Ant Colony Algorithm for Constrained Multi-objective Optimization ProblemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-01-24Full publication date if available
- Authors
-
Yan-mei LUO, Guoyan YuList of authors in order
- Landing page
-
https://doi.org/10.12783/dtcse/msota2018/27589Publisher landing page
- PDF URL
-
https://dpi-proceedings.com/index.php/dtcse/article/download/27589/26999Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://dpi-proceedings.com/index.php/dtcse/article/download/27589/26999Direct OA link when available
- Concepts
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Ant colony optimization algorithms, Mathematical optimization, Sorting, Pareto principle, sort, Computer science, Path (computing), Multi-objective optimization, Set (abstract data type), Algorithm, Optimization problem, Constraint (computer-aided design), Mathematics, Geometry, Information retrieval, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2019: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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