Sammendrag
When solving problems in the real world using optimization tools, the model solved
by the tools is often only an approximation of the underlying, real, problem. In these circumstances,
a decision maker (DM) should consider a diverse set of good solutions, not just
an optimal solution as produced using the model. On the other hand, the same DM will only
be interested in seeing a few of the alternative solutions, and not the plethora of solutions
often produced by modern search techniques. There is thus a need to distinguish between
good solutions using the attributes of solutions. We develop a distance function of the type
proposed in the Psychology literature by Tversky (1977) for the class of VRP problems. We
base our difference on the underlying structure of solutions.
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