Name
Abstract | ||
|---|---|---|
An Environmental Adaption Method (EAM) has been recently proposed in which, each solution updates its structure on the basis of current environmental fitness and its own fitness. EAM uses a new operator known as adaption operator. In this paper, an improved EAM, henceforth called as IEAM has been proposed and proper tuning of parameters of algorithm has been done to find the optimal solution in minimum time. IEAM has been tested on a set of benchmark functions. Results show the superiority of IEAM over PSO-TVAC, SADE and other optimization algorithms. Even for complex functions, the performance of IEAM is very good. In addition to this, IEAM has also been applied to software testing to generate test cases for white box testing. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3233/IFS-141195 | Journal of Intelligent and Fuzzy Systems |
Keywords | Field | DocType |
evolutionary computing,improved eam,pso | Computer science,Evolutionary computation,White-box testing,Optimization algorithm,Test case,Artificial intelligence,Operator (computer programming),Minimum time,Software testing | Journal |
Volume | Issue | ISSN |
27 | 5 | 1064-1246 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. K. Mishra | 1 | 40 | 7.98 |
| Shailesh Tiwari | 2 | 14 | 6.95 |
| Arun Kumar Misra | 3 | 42 | 6.08 |