Abstract
There are many problems in the real world that can be modeled as large scale global optimization problems. Usually, large scale global optimization problems are global optimization problems where the dimensions are greater than or equal to 1000. In this research, we propose a genetic algorithm that can be used to solve large scale optimization problems with dimensions up to 100000. To measure the capabilities of the proposed genetic algorithm, we use five different test functions. Based on the results obtained, it can be inferred that the proposed genetic algorithm can find a good solution in a fairly short time.
| Original language | English |
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| Article number | 012055 |
| Journal | Journal of Physics: Conference Series |
| Volume | 1821 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 29 Mar 2021 |
| Event | 6th International Conference on Mathematics: Pure, Applied and Computation, ICOMPAC 2020 - Surabaya, Virtual, Indonesia Duration: 24 Oct 2020 → … |