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An Opposition-Based Evolutionary Algorithm for Many-Objective Optimization with Adaptive Clustering Mechanism
- Source :
- Computational Intelligence and Neuroscience, Vol 2019 (2019), Computational Intelligence and Neuroscience
- Publication Year :
- 2019
- Publisher :
- Hindawi Limited, 2019.
-
Abstract
- Balancing convergence and diversity has become a key point especially in many-objective optimization where the large numbers of objectives pose many challenges to the evolutionary algorithms. In this paper, an opposition-based evolutionary algorithm with the adaptive clustering mechanism is proposed for solving the complex optimization problem. In particular, opposition-based learning is integrated in the proposed algorithm to initialize the solution, and the nondominated sorting scheme with a new adaptive clustering mechanism is adopted in the environmental selection phase to ensure both convergence and diversity. The proposed method is compared with other nine evolutionary algorithms on a number of test problems with up to fifteen objectives, which verify the best performance of the proposed algorithm. Also, the algorithm is applied to a variety of multiobjective engineering optimization problems. The experimental results have shown the competitiveness and effectiveness of our proposed algorithm in solving challenging real-world problems.
- Subjects :
- Scheme (programming language)
Mathematical optimization
Optimization problem
Article Subject
General Computer Science
Computer science
General Mathematics
0208 environmental biotechnology
Evolutionary algorithm
02 engineering and technology
lcsh:Computer applications to medicine. Medical informatics
Engineering optimization
lcsh:RC321-571
Convergence (routing)
0202 electrical engineering, electronic engineering, information engineering
Cluster Analysis
Computer Simulation
Cluster analysis
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Problem Solving
computer.programming_language
General Neuroscience
Sorting
General Medicine
Biological Evolution
020801 environmental engineering
Variety (cybernetics)
lcsh:R858-859.7
020201 artificial intelligence & image processing
computer
Algorithms
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 16875273 and 16875265
- Volume :
- 2019
- Database :
- OpenAIRE
- Journal :
- Computational Intelligence and Neuroscience
- Accession number :
- edsair.doi.dedup.....958543a58e97c17806d5273b2c40813c