Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
This contribution proposes an enhanced and generic selection model for Genetic Algorithms (GAs) and Genetic Programming (GP) which is able to preserve the alleles which are part o...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
Genetic algorithms (GAs) are efficient non-gradient stochastic search methods. Parallel GAs are proposed to overcome the deficiencies of sequential GAs, such as low speed and aptn...
Baowen Xu, Yu Guan, Zhenqiang Chen, Karl R. P. H. ...
Many of today’s embedded systems, such as wireless and portable devices rely heavily on the limited power supply. Therefore, energy efficiency becomes one of the major design con...
The problem of test generation belongs to the class of NP-complete problems and it is becoming more and more di cult as the complexity of VLSI circuits increases, and as long as e...
Dilip Krishnaswamy, Michael S. Hsiao, Vikram Saxen...