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Parallel Shared-Memory Multi-Objective Stochastic Search for Competitive Facility Location

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 8805)

Abstract

A stochastic search algorithm for local multi-objective optimization is developed and applied to solve a multi-objective competitive facility problem for firm expansion using shared-memory parallel computing systems. The performance of the developed algorithm is experimentally investigated by solving competitive facility location problems, using up to 16 shared-memory processing units. It is shown that the developed algorithm has advantages against its precursor in the sense of the precision of optimization and that it has almost linear speed-up on 16 shared-memory processing units, when solving competitive facility location problems of different scope reasonable for practical applications.

Keywords

  • Facility Location
  • Multi-Objective Optimization
  • Stochastic Search
  • Shared Memory Parallel Computing

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Lančinskas, A., Ortigosa, P.M., Žilinskas, J. (2014). Parallel Shared-Memory Multi-Objective Stochastic Search for Competitive Facility Location. In: , et al. Euro-Par 2014: Parallel Processing Workshops. Euro-Par 2014. Lecture Notes in Computer Science, vol 8805. Springer, Cham. https://doi.org/10.1007/978-3-319-14325-5_7

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  • DOI: https://doi.org/10.1007/978-3-319-14325-5_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14324-8

  • Online ISBN: 978-3-319-14325-5

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