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Parallel Multi-objective Memetic Algorithm for Competitive Facility Location

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 8385)

Abstract

A hybrid genetic algorithm for global multi-objective optimization is parallelized and applied to solve competitive facility location problems. The impact of usage of the local search on the performance of the parallel algorithm has been investigated. An asynchronous version of the parallel genetic algorithm with the local search has been proposed and investigated by solving competitive facility location problem utilizing hybrid distributed and shared memory parallel programming model on high performance computing system.

Keywords

  • Facility location
  • Multi-objective optimization
  • Memetic algorithms

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Acknowledgments

This research was funded by a Grant (No. MIP-063/2012) from the Research Council of Lithuania.

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Correspondence to Algirdas Lančinskas .

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Lančinskas, A., Žilinskas, J. (2014). Parallel Multi-objective Memetic Algorithm for Competitive Facility Location. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2013. Lecture Notes in Computer Science(), vol 8385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55195-6_33

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  • DOI: https://doi.org/10.1007/978-3-642-55195-6_33

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