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Solution of Multi-Objective Competitive Facility Location Problems Using Parallel NSGA-II on Large Scale Computing Systems

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7782)

Abstract

The multi-objective firm expansion problem on competitive facility location model, and an evolutionary algorithm suitable to solve multi-objective optimization problems are reviewed in the paper. Several strategies to parallelize the algorithm utilizing both the distributed and shared memory parallel programing models are presented. Results of experimental investigation carried out by solving the competitive facility location problem using up to 2048 processing units are presented and discussed.

Keywords

  • Multi-objective Optimization
  • Parallel Pareto Ranking
  • Parallel Non-dominated Sorting Genetic Algorithm
  • Competitive Facility Location Problem

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Lančinskas, A., Żilinskas, J. (2013). Solution of Multi-Objective Competitive Facility Location Problems Using Parallel NSGA-II on Large Scale Computing Systems. In: Manninen, P., Öster, P. (eds) Applied Parallel and Scientific Computing. PARA 2012. Lecture Notes in Computer Science, vol 7782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36803-5_31

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  • DOI: https://doi.org/10.1007/978-3-642-36803-5_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36802-8

  • Online ISBN: 978-3-642-36803-5

  • eBook Packages: Computer ScienceComputer Science (R0)