### Evolutionary Multiobjective Optimization with a Segment-Based External Memory Support for the Multiobjective Quadratic Assignment Problem

Abstract

Multiobjective evolutionary optimization has been demonstrated to be an efficient
method for some difficult multiobjective optimization problems; particularly the
quadratic assignment problem which is a provably difficult NP-complete problem
with a multitude of real-world applications. This paper introduces the use of a
segment-based external memory in evolutionary multiobjective optimization. In
principle, variable-size solution segments taken from a number of previously
promising solutions are stored in an external memory whose elements are used
in the construction of new solutions. In the construction of a solution, a solution
segment is retrieved from the external memory and used in the construction of
complete solutions through evolutionary recombination operators. The aim is to
provide further intensification around promising solutions without weakening the
exploration capabilities. Different instances of the multiobjective quadratic assignment
problem are used for performance evaluations and, almost in all trials, the proposed
external memory strategy provided significantly better results than the multiobjective
genetic algorithm (MOGA).