Franz Rothlauf.
Representations for Genetic and Evolutoinary Algorithms.
Springer. 2002
In the field of genetic and evolutionary algorithms (GEAs),
much theory and empirical study has been heaped upon operators and test problems,
but problem representation has often been taken as given.
This monograph breaks with this tradition and studies a number of critical elements
of a theory of representations for GEAs and applies them to
the empirical study of various important idealized test functions
and problems of commercial importance.
The book considers basic concepts of representations, such as redundancy,
scaling and locality and describes how GEAs’ performance is influenced.
Using the developed theory representations can be analyzed and designed
in a theory-guided manner.
The theoretical concepts are used as examples for efficiently solving
integer optimization problems and network design problems.
The results show that proper representations are crucial for GEAs’ success.
