  Understanding the behaviour of heuristic search methods is a challenge. This
even holds for simple local search methods such as 2-OPT for the Traveling
Salesperson problem. In this paper, we present a general framework that is able
to construct a diverse set of instances that are hard or easy for a given
search heuristic. Such a diverse set is obtained by using an evolutionary
algorithm for constructing hard or easy instances that are diverse with respect
to different features of the underlying problem. Examining the constructed
instance sets, we show that many combinations of two or three features give a
good classification of the TSP instances in terms of whether they are hard to
be solved by 2-OPT.
