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

  • Algirdas Lančinskas
  • Pilar Martínez Ortigosa
  • Julius Žilinskas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Algirdas Lančinskas
    • 1
  • Pilar Martínez Ortigosa
    • 2
  • Julius Žilinskas
    • 1
  1. 1.Institute of Mathematics and InformaticsVilnius UniversityVilniusLithuania
  2. 2.Universidad de Almería, ceiA3AlmeríaSpain

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