Abstract
Inspired by the biological evolution, local cooperation behaviors have been modeled in function optimizations for providing effective search methods. This paper proposes a new meta-heuristic algorithm named Neighborhood Field Optimization algorithm (NFO), which totally utilizes the local cooperation of individuals. This paper also analyzes how the local cooperation helps optimization, which is modeled as the neighborhood field. The proposed NFO is compared with other widely used evolutionary algorithms in intensive simulation under different benchmark functions. The presented results show that NFO is able to solve multimodal problems globally, and thus the cooperation behavior is proven its significance to model a search method. © 2012 Springer-Verlag Berlin Heidelberg.
| Original language | English |
|---|---|
| Pages (from-to) | 819-834 |
| Journal | Soft Computing |
| Volume | 17 |
| Issue number | 5 |
| Online published | 6 Dec 2012 |
| DOIs | |
| Publication status | Published - May 2013 |
Research Keywords
- Contour gradient optimization
- Evolutionary algorithm
- Local search
- Neighborhood field
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