Parallel Multi-objective Memetic Algorithm for Competitive Facility Location

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8385)


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.


Facility location Multi-objective optimization Memetic algorithms 



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


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Institute of Mathematics and InformaticsVilnius UniversityVilniusLithuania

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