A well-designed fitness function is essential to the effectiveness and efficiency of evolutionary testing. Fitness function design has been researched extensively. For fitness ...
Yan Wang, Zhiwen Bai, Miao Zhang, Wen Du, Ying Qin...
We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two r...
Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often t...
This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of...
A Local Linear Embedding (LLE) module enhances the performance of two Evolutionary Computation (EC) algorithms employed as search tools in global optimization problems. The LLE em...