Abstract
Some optimization algorithms based on theories from immunology have the feature of finding an arbitrary number of optima, including the global solution. However, this advantage comes at the cost of a large number of objective function evaluations, in most cases, prohibitive in electromagnetic design. This paper proposes a modified version of the artificial immune network algorithm (opt-AINet) for electromagnetic design optimization. The objective of this modified AINet (m-AINet) is to reduce the computational effort required by the algorithm, while keeping or improving the convergence characteristics. Another improvement proposed is to make it more suitable for constrained problems through the utilization of a specific constraint-handling technique. The results obtained over an analytical problem and the design of an electromagnetic device show the applicability of the proposed algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 1111-1114 |
| Number of pages | 4 |
| Journal | IEEE Transactions on Magnetics |
| Volume | 42 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Apr 2006 |
Funding
This work was supported by the National Council of Scientific and Technologic Development - CNPq - under Grant 141731/2004-4 and Grant 300353/1997-9, Brazil, and by the Ministry of Education, Culture, Sports, Science and Technology: MEXT, Japan.
Keywords
- Artificial immune systems
- Electromagnetic design optimization
- Immune networks
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