With technology scaling down to 90nm and below, many yield-driven design and optimization methodologies have been proposed to cope with the prominent process variation and to incr...
Fang Gong, Hao Yu, Yiyu Shi, Daesoo Kim, Junyan Re...
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Many state-of-the-art approaches on fault-tolerant system design make the simplifying assumption that all faults are detected within a certain time interval. However, based on a d...
Jia Huang, Kai Huang, Andreas Raabe, Christian Buc...
Discovering the dependencies among the variables of a domain from examples is an important problem in optimization. Many methods have been proposed for this purpose, but few large...
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...