Analysing a hybrid model-based evolutionary algorithm for a hard grouping problem

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Abstract

We present a new hybrid model-based algorithm called Memetic Path Relinking (MemPR). MemPR incorporates ideas of memetic, evolutionary, model-based algorithms and path relinking. It uses different operators that compete to fill a small population of high quality solutions. We present a new hard grouping problem derived from a real world transport lot building problem. In order to better understand the algorithm as well as the problem we analyse the impact of the different operators on solution quality and which operators perform best at which stage of optimisation. Finally we compare MemPR to other state-of-the-art algorithms and find that MemPR outperforms them on real-world problem instances.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers
EditorsRoberto Moreno-Diaz, Alexis Quesada-Arencibia, Franz Pichler
PublisherSpringer Verlag
Pages347-354
Number of pages8
ISBN (Print)9783319747170
DOIs
Publication statusPublished - 2018
Event16th International Conference on Computer Aided Systems Theory, EUROCAST 2017 - Las Palmas de Gran Canaria, Spain
Duration: 19 Feb 201724 Feb 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10671 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Computer Aided Systems Theory, EUROCAST 2017
CountrySpain
CityLas Palmas de Gran Canaria
Period19.02.201724.02.2017

Keywords

  • Estimation of distribution algorithm
  • Grouping problem
  • Hybrid algorithm
  • Memetic algorithm

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