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An Improved Memetic Algorithm for the Antibandwidth Problem

  • Eduardo Rodriguez-Tello
  • Luis Carlos Betancourt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7401)

Abstract

This paper presents an Improved Memetic Algorithm (IMA) designed to compute near-optimal solutions for the antibandwidth problem. It incorporates two distinguishing features: an efficient heuristic to generate a good quality initial population and a local search operator based on a Stochastic Hill Climbing algorithm. The most suitable combination of parameter values for IMA is determined by employing a tunning methodology based on Combinatorial Interaction Testing. The performance of the fine-tunned IMA algorithm is investigated through extensive experimentation over well known benchmarks and compared with an existing state-of-the-art Memetic Algorithm, showing that IMA consistently improves the previous best-known results.

Keywords

Memetic Algorithms Antibandwidth Problem Combinatorial Interaction Testing Parameter Tunning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Eduardo Rodriguez-Tello
    • 1
  • Luis Carlos Betancourt
    • 1
  1. 1.Information Technology LaboratoryCINVESTAV-TamaulipasVictoria Tamps.Mexico

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