1. What are the contributions mentioned in the paper "Evolutionary multiobjective optimization with a segment-based external memory support for the multiobjective quadratic assignment problem" ?
This paper introduces the use of a segment-based external memory in evolutionary multiobjective optimization.. 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 ).. 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.
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2. What is the purpose of this study?
In this study, the use of an external memory implementation in evolutionary multiobjective optimization is introduced towards improving their search capability and solution quality.
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3. How many individuals are used in conventional MOGAs?
Experiments are carried out using a population sizeGenomeObjective ValuesObjective Valuesof 400 individuals for conventional MOGAs.
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4. What is the mutation operator used to modify the parent-only genes?
A mutation operator is used to modify those parent-only genes, while genes of the inserted sequences remain unmodified, and the mutation rate is 0.06.
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