Abstract
We present a hybrid heuristic methodology for the
solution of the multi-objective cell-formation problem.
Traditional optimisation methodologies employ
aggregating schemes in order to transform the problem
into a single-objective case. In this way the designer
is not presented with a set of non-dominated solutions
but with a single compromise solution based on
pre-specified weighting priorities. The proposed
methodology combines a traditional hierarchical
clustering analysis technique with a genetic
programming algorithm that is based on the principles
of evolutionary computation. The hybrid methodology
evolves an approximation of the Pareto set of solutions
for multi-objective cell-formation problems. The
benefits brought by the proposed approach in comparison
to traditional optimisation methodologies are
illustrated using a typical example taken from the
literature
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