In this paper we provide a review of the current state of research on Portfolio Management
with the support of Multiobjective Evolutionary Algorithms (MOEAs). Second we present a …

This article surveys the most relevant kriging-based infill algorithms for multiobjective
simulation optimization. These algorithms perform a sequential search of so-called infill …

This article provides a general overview of the field now known as" evolutionary multi-
objective optimization," which refers to the use of evolutionary algorithms to solve problems …

Over the last decade, a variety of evolutionary algorithms (EAs) have been proposed for
solving multiobjective optimization problems. Especially more recent multiobjective …

MOEAs are getting immense popularity in the recent past, mainly because of their ability to
find a wide spread of Pareto-optimal solutions in a single simulation run. Various …

A large number of methods for solving multiobjective optimisation (MOO) problems have
been developed. To compare these methods rigorously, or to measure the performance of a …

The growing popularity of multiobjective evolutionary algorithms (MOEAs) for solving many-
objective problems warrants the careful investigation of their search controls and failure …

The knapsack problem (KP) and its multidimensional version (MKP) are basic problems in
combinatorial optimization. In this paper, we consider their multiobjective extension (MOKP …

In this work, we present a method, called Two-Phase Pareto Local Search, to find a good
approximation of the efficient set of the biobjective traveling salesman problem. In the first …

This chapter presents a brief review of some of the most relevant research currently taking
place in evolutionary multiobjective optimization. The main topics covered include …