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A GPU-based genetic algorithm for the p-median problem

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Abstract

The p-median problem is a well-known NP-hard problem. Many heuristics have been proposed in the literature for this problem. In this paper, we exploit a GPGPU parallel computing platform to present a new genetic algorithm implemented in CUDA and based on a pseudo-Boolean formulation of the p-median problem. We have tested the effectiveness of our algorithm using a Tesla K40 (2880 CUDA cores) on 290 different benchmark instances obtained from OR-Library, discrete location problems benchmark library, and benchmarks introduced in recent publications. The algorithm succeeded in finding optimal solutions for all instances except for two OR-library instances, namely pmed 30 and pmed 40, where better than 99.9% approximations were obtained.

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Notes

  1. We shall use distance and cost interchangeably.

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Authors and Affiliations

  1. Computer Science Department, Kuwait University, P. O. Box 5969, Safat, 13060, Kuwait City, Kuwait

    Bader F. AlBdaiwi & Hosam M. F. AboElFotoh

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  1. Bader F. AlBdaiwi
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  2. Hosam M. F. AboElFotoh
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Correspondence to Bader F. AlBdaiwi.

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AlBdaiwi, B.F., AboElFotoh, H.M.F. A GPU-based genetic algorithm for the p-median problem. J Supercomput 73, 4221–4244 (2017). https://doi.org/10.1007/s11227-017-2006-x

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