Name
Title | ||
|---|---|---|
Equality Constraint-Handling Technique with Variables Grouping in EA for Large Scale Global Optimization |
Abstract | ||
|---|---|---|
In the constrained or the unconstrained large scale global optimization problems, it is difficult to find the optimal solution by using most existing evolutionary algorithms. For the equality constrained large scale global optimization problem, we propose the new technique that groups variables to each of subcomponents and handles the equality constraint by using trigonometric functions. In use of our technique, the evolutionary algorithms effectively find good feasible solutions without evolutionary stagnation because the transformed unconstrained search space consists only of feasible solutions. In numerical experiments, for a portfolio replication problem, we demonstrate the effectiveness of our technique. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SMC.2018.00057 | 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) |
Keywords | Field | DocType |
equality constraint-handling technique,optimal solution,evolutionary stagnation,portfolio replication problem,evolutionary algorithms,global optimization problem | Mathematical optimization,Trigonometric functions,Global optimization,Evolutionary algorithm,Computer science,Portfolio,Artificial intelligence,Machine learning,Global optimization problem | Conference |
ISSN | ISBN | Citations |
1062-922X | 978-1-5386-6651-7 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yukiko Orito | 1 | 13 | 7.69 |
| Yoshiko Hanada | 2 | 20 | 11.42 |