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A Modified Continuous Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem

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Information Technology and Mobile Communication (AIM 2011)

Abstract

A continuous version of particle swarm optimization (CPSO) is employed to solve uncapacitated facility location (UFL) problem which is one of the most widely studied in combinatorial optimization. The basic algorithm had already been published in the Research Article “A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem” [1]. But in addition to that, the algorithm is slightly modified here to get better result in a lesser time. To make a reasonable comparison, the same benchmark suites that are collected from OR-library [6] are applied here. In conclusion, the results showed that this modified CPSO algorithm is slightly better than the published CPSO algorithm.

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References

  1. Guner Ali, R., Mehmet, S.: A Discrete Particle Swarm Optimization Algorithm For Uncapacitated Facility Location Problem. Hindawi Publishing Corporation Journal of Artificial Evolution And Applications 2008, Article ID 861512, 9 (2008), doi:10.1155/2008/861512

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  2. Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm Intelligence. Morgan Kaufmann, San Francisco (2001)

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  3. Ghosh, D.: Neighborhood search heuristics for the uncapacitated facility location problem. European Journal of Operational Research 150(1), 150–162 (2003)

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  4. Eberhart, R.C., Kennedy, J.: New optimizer using particle swarm theory. In: Proceedings of the 6th International Symposium on Micro Machine and Human Science (MHS 1995), Nagoya, Japan, October 1995, pp. 39–43 (1995)

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  5. Beasley, J.E.: OR-Library (2005), http://people.brunel.ac.uk/mastjjb/jeb/info.html

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© 2011 Springer-Verlag Berlin Heidelberg

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Saha, S., Kole, A., Dey, K. (2011). A Modified Continuous Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem. In: Das, V.V., Thomas, G., Lumban Gaol, F. (eds) Information Technology and Mobile Communication. AIM 2011. Communications in Computer and Information Science, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20573-6_52

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  • DOI: https://doi.org/10.1007/978-3-642-20573-6_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20572-9

  • Online ISBN: 978-3-642-20573-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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