Abstract. In engineering and other ‘real-world’ applications, multiobjective optimization problems must frequently be tackled on a tight evaluation budget — tens or hundreds ...
With the invention of microarray technology, researchers are able to measure the expression levels of ten thousands of genes in parallel at various time points of a biological proc...
Christian Spieth, Felix Streichert, Nora Speer, An...
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their si...
This paper studies the strategies for multi-objective optimization in a dynamic environment. In particular, we focus on problems with objective replacement, where some objectives ...