Proceedings of the Genetic and Evolutionary Computation Conference Companion:
Difficulties in fair performance comparison of mul Page 1 1 Difficulties in Fair Performance …

Multimodality is commonly seen in real-world multiobjective optimization problems (MOPs).
In such optimization problems, namely, multimodal MOPs (MMOPs), multiple decision …

Subset selection plays an important role in the field of evolutionary multiobjective
optimization (EMO). Especially, in an EMO algorithm with an unbounded external archive …

This book presents an overview of several archiving strategies we have developed over the
last years dealing with approximations of the solution sets of multi-objective optimization …

Multi-objective evolutionary algorithms (MOEAs) have been successfully applied for the
numerical treatment of multi-objective optimization problems (MOP) during the last three …

Subset selection is an important component in evolutionary multiobjective optimization
(EMO) algorithms. Clustering, as a classic method to group similar data points together, has …

Evolutionary multi-objective optimization (EMO) is a highly active research field that has
attracted many researchers and practitioners over the past three decades. Surprisingly, until …

Hypervolume subset selection is a hot topic in the field of evolutionary multi-objective
optimization (EMO) due to the increasing needs of selecting a small set of representative …

Abstract The Next Release Problem (NRP) is a combinatorial optimization problem that aims
to find a subset of software requirements to be delivered in the next software release, which …

One important issue in evolutionary multi-objective optimization (EMO) which still leaves
room for improvement is the maintenance of the subset of the obtained candidate solutions …