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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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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.

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References

  1. Hotelling, H.: Stability in competition. Economic Journal 39, 41–57 (1929)

    Article  Google Scholar 

  2. Eiselt, H., Laporte, G.: Sequential location problems. European Journal of Operational Research 96, 217–231 (1996)

    Article  Google Scholar 

  3. Eiselt, H., Laporte, G., Thisse, J.F.: Competitive location models: a framework and bibliography. Transportation Science 27(1), 44–54 (1993)

    Article  MATH  Google Scholar 

  4. Plastria, F.: Static Competitive Facility Location: An Overview of Optimisation Approaches. European Journal of Operational Research 129(3), 461–470 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  5. Sáiz, M.E., Hendrix, E.M.T., Fernández, J., Pelegrín, B.: On a branch-and-bound approach for a Huff-like Stackelberg location problem. OR Spectrum 31, 679–705 (2009)

    Article  MATH  Google Scholar 

  6. Tóth, B., Fernández, J., Pelegrín, B., Plastria, F.: Sequential versus simultaneous approach in the location and design of two new facilities using planar Huff-like models. Journal of Operational Research 36(5), 1393–1405 (2009)

    MATH  Google Scholar 

  7. Huff, D.L.: Defining and estimating a trade area. Journal of Marketing 28, 34–38 (1964)

    Article  Google Scholar 

  8. Huff, D.L.: A programmed solution for approximating an optimum retail location. Land Economics 42, 293–303 (1966)

    Article  Google Scholar 

  9. Drezner, T.: Locating a single new facility among existing unequally attractive facilities. Journal Regional Science 34(2), 237–252 (1994)

    Article  MathSciNet  Google Scholar 

  10. Plastria, F.: Profit maximising single competitive facility location in the plane. Studies in Locational Analysis 11, 115–126 (1997)

    MathSciNet  MATH  Google Scholar 

  11. Plastria, F., Carrizosa, E.: Optimal location and design of a competitive facility. Mathematical Programming 100, 247–265 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  12. Redondo, J.L., Fernández, I.G., Ortigosa, P.: Heuristics for the facility location and design (1j1)-centroid problem on the plane. Computational Optimization and Applications 45(1), 111–141 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  13. Srinivas, N., Deb, K.: Multi-Objective Function Optimization Using Non-dominated Sorting Genetic Algorithms. Evolutionary Computation 2(3), 221–248 (1995)

    Article  Google Scholar 

  14. Mitra, K., Deb, K., Gupta, S.K.: Multiobjective Dynamic Optimization of an Industrial Nylon 6 Semibatch Reactor Using Genetic Algorithms. Journal of Applied Polymer Science 69(1), 69–87 (1998)

    Article  Google Scholar 

  15. Weile, D.S., Michielssen, E., Goldberg, D.E.: Genetic Algorithm Design of pareto-optimal Broad Band Microwave Absorbers. IEEE Transactions on Electromagnetic Compatibility 38(4), 518–525 (1996)

    Article  Google Scholar 

  16. Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. In: Deb, K., Rudolph, G., Lutton, E., Merelo, J.J., Schoenauer, M., Schwefel, H.-P., Yao, X. (eds.) PPSN 2000. LNCS, vol. 1917, pp. 849–858. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  17. Amdahl, G.M.: Validity of the single-processor approach to achieving large scale computing capabilities. In: AFIPS Conference Proceedings, vol. 30, pp. 483–485 (1967)

    Google Scholar 

  18. Durillo, J.J., Nebro, A.J., Luna, F., Alba, E.: A study of master-slave approaches to parallelize NSGA-II. In: IEEE International Symposium on Parallel and Distributed Processing, pp. 14–18 (2008)

    Google Scholar 

  19. Coello, C.C., Lamont, G.B., Veldhuizen, D.A. (eds.): Evolutionary Algorithms for Solving Multi-Objective Problems, 2nd edn. (2007)

    Google Scholar 

  20. Lančinskas, A., Žilinskas, J.: Approaches to Parallelize pareto Ranking in NSGA-II Algorithm. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds.) PPAM 2011, Part II. LNCS, vol. 7204, pp. 371–380. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Informatics, Vilnius University, Akademijos 4, 08663, Vilnius, Lithuania

    Algirdas Lančinskas & Julius Żilinskas

Authors
  1. Algirdas Lančinskas
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  2. Julius Żilinskas
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Editor information

Editors and Affiliations

  1. CSC - IT Center for Science, 02101, Espoo, Finland

    Pekka Manninen  & Per Öster  & 

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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)

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