Memetic Algorithm with Hungarian Matching Based Crossover and Diversity Preservation

Authors

  • Emmanuel Romero Ruiz Universidad de Guanajuato, Guanajuato
  • Carlos Segura Centro de Investigación en Matemáticas (CIMAT), Área de Computación, Guanajuato

DOI:

https://doi.org/10.13053/cys-22-2-2951

Keywords:

graph partitioning problem, memetic algorithm, diversity preservation, maximum matching

Abstract

The Graph Partitioning Problem (GPP) is a well-known NP-hard combinatorial problem that involves the finding of a partition of vertexes that minimizes the number of cut edges while fulfilling a set of constraints. This paper presents a newly designed optimizer for the GPP: the Memetic Algorithm with Hungarian Matching Based Crossover and Diversity Preservation (MAHMBCDP). MAHMBCDP is a population-based scheme that incorporates an explicit mechanism to control the diversity with the aim of making a proper use of resources when dealing with long-termexecutions. Among the novelties of our proposal, the design of a crossover operator that is based on the Hungarian Algorithm to calculate a maximum matching is particularly important. Experimental validation with a set of well-known instances of the graph partitioning archive shows the proper performance of our proposal. In fact, new best-known solutions could be attained inten test cases.

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Published

2018-06-29

Issue

Vol. 22 No. 2 (2018): Thematic Issue on Numerical and Evolutionary Optimization (Guest editors: L. Trujillo, Y. Maldonado, O. Schuetze)

Section

Articles of the Thematic Issue

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