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Probability Distribution of Solution Time in GRASP: An Experimental Investigation

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Abstract

A GRASP (greedy randomized adaptive search procedure) is a multi-start metaheuristic for combinatorial optimization. We study the probability distributions of solution time to a sub-optimal target value in five GRASPs that have appeared in the literature and for which source code is available. The distributions are estimated by running 12,000 independent runs of the heuristic. Standard methodology for graphical analysis is used to compare the empirical and theoretical distributions and estimate the parameters of the distributions. We conclude that the solution time to a sub-optimal target value fits a two-parameter exponential distribution. Hence, it is possible to approximately achieve linear speed-up by implementing GRASP in parallel.

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Authors and Affiliations

  1. Department of Computer Science, Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, RJ, 22453-900, Brazil

    Renata M. Aiex & Celso C. Ribeiro

  2. AT&;T Labs Research, Information Sciences Research Center, Florham Park, NJ, 07932, USA

    Mauricio G.C. Resende

Authors
  1. Renata M. Aiex
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  2. Mauricio G.C. Resende
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  3. Celso C. Ribeiro
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Aiex, R.M., Resende, M.G. & Ribeiro, C.C. Probability Distribution of Solution Time in GRASP: An Experimental Investigation. Journal of Heuristics 8, 343–373 (2002). https://doi.org/10.1023/A:1015061802659

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