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On the Advantages of Searching Infeasible Regions in Constrained Evolutionary-Based Multi-Objective Engineering Optimization.
- Source :
-
Journal of Mechanical Design . Apr2024, Vol. 146 Issue 4, p1-11. 11p. - Publication Year :
- 2024
-
Abstract
- Solving a multiple-criteria optimization problem with severe constraints remains a significant issue in multi-objective evolutionary algorithms. The problem primarily stems from the need for a suitable constraint handling technique. One potential approach is balancing the search in feasible and infeasible regions to find the Pareto front efficiently. The justification for such a strategy is that the infeasible region also provides valuable information, especially in problems with a small percentage of feasibility areas. To that end, this paper investigates the potential of the infeasibility-driven principle based on multiple constraint ranking-based techniques to solve a multi-objective problem with a small feasibility ratio. By analyzing the results from intensive experiments on a set of test problems, including the realistic multi-objective car structure design and actuator design problem, it is shown that there is a significant improvement gained in terms of convergence by utilizing the generalized version of the multiple constraint ranking techniques. [ABSTRACT FROM AUTHOR]
- Subjects :
- *EVOLUTIONARY algorithms
*ENGINEERING
*PROBLEM solving
*ENGINEERING design
Subjects
Details
- Language :
- English
- ISSN :
- 10500472
- Volume :
- 146
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Journal of Mechanical Design
- Publication Type :
- Academic Journal
- Accession number :
- 176488104
- Full Text :
- https://doi.org/10.1115/1.4063629