Abstract:
Real-world optimisation problems are often very complex. Metaheuristics have been successful
in solving many of these problems, but the difficulty in choosing the best approach
can be a huge challenge for practitioners. One approach to this dilemma is to use fitness
landscape analysis to better understand problems before deciding on approaches to solving
the problems. However, despite extensive research on fitness landscape analysis and a
large number of developed techniques, very few techniques are used in practice. This could
be because fitness landscape analysis in itself can be complex. In an attempt to make fitness
landscape analysis techniques accessible, this paper provides an overview of techniques
from the 1980s to the present. Attributes that are important for practical
implementation are highlighted and ways of adapting techniques to be more feasible or
appropriate are suggested. The survey reveals the wide range of factors that can influence
problem difficulty, emphasising the need for a shift in focus away from predicting problem
hardness towards measuring characteristics. It is hoped that this survey will invoke
renewed interest in the field of understanding complex optimisation problems and ultimately
lead to better decision making on the use of appropriate metaheuristics.
