ABSTRACT
This chapter presents a basic introduction to Evolutionary Multiobjective Optimization (EMO), focusing on its main concepts, the most popular algorithms in current use, and some of its applications. It provides some basic concepts from multiobjective optimization and the use of evolutionary algorithms in multiobjective optimization. The chapter describes some of the main topics of research that are currently attracting a lot of attention in the EMO field and provides a set of sample applications of multiobjective evolutionary algorithms (MOEAs). It discusses some of the main topics of research in the EMO field that currently attract a lot of attention. MOEAs extend a traditional evolutionary algorithm in two main aspects: the selection mechanism and a diversity maintenance mechanism. A number of methods have been proposed in the literature to maintain diversity in an eigenstructure assignment. The existence of challenging, but solvable problems, is a key issue to preserve the interest in a research discipline.
