Name
Abstract | ||
|---|---|---|
Bacterial foraging optimizer (BFO) is predominately used to find solutions for real-world problems. One of the major characteristics of BFO is the chemotactic movement of a virtual bacterium that models a trial solution of the problems. It is pointed out that the chemotaxis employed by classical BFO usually results in sustained oscillation, especially on flat fitness landscapes, when a bacterium cell is close to the optima. In this paper we propose a novel adaptive computational chemotaxis based on the concept of field, in order to accelerate the convergence speed of the group of bacteria near the tolerance. Firstly, a simple scheme is designed for adapting the chemotactic step size of each field which is comprised of two or three dimensional space. Then, the scheme chooses the fields which perform better to boost further the convergence speed. Empirical simulations over several numerical benchmarks demonstrate that BFO with adaptive chemotactic operators based on field has better convergence behavior, as compared against other versions of adaptive BFO. © 2012 IEEE. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICNC.2012.6234671 | ICNC |
Keywords | Field | DocType |
bacterial foraging,computational chemotaxis,field,global optimization,swam intelligence,bfo,three dimensional,optimization,oscillations,microorganisms,convergence,cell motility,fitness landscape,benchmark testing | Convergence (routing),Three-dimensional space,Mathematical optimization,Fitness landscape,Global optimization,Computer science,Operator (computer programming),Chemical technology,Foraging | Conference |
Volume | Issue | Citations |
null | null | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Xu | 1 | 1365 | 100.22 |
| Yanheng Liu | 2 | 228 | 36.14 |
| Aimin Wang | 3 | 78 | 8.88 |
| Gang Wang | 4 | 223 | 13.31 |
| Hui-Ling Chen | 5 | 184 | 9.24 |