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Sequential and Parallel Hybrid Approaches of Augmented Neural Networks and GRASP for the 0-1 Multidimensional Knapsack Problem

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Computational Science and Its Applications – ICCSA 2016 (ICCSA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9787))

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Abstract

There are a lot of problems, whose solutions are based on 0-1 multidimensional problem. Since this combinatorial optimization problem is \(\mathcal {NP}\)-hard, one of the approaches to solve it is the use of metaheuristics. For this problem, even heuristics consume a lot of time to find a solution, which motivates the search for alternatives capable of making the use of such techniques less time-consuming. Among these alternatives, the use of parallelization strategies deserves to be highlighted, once it may lead to reduced execution times and/or better quality results. In this work we propose a hybrid approach of augmented neural networks and GRASP for the 0-1 multidimensional knapsack problem, we describe a sequential and a GPGPU implementation and measure the achieved speedups. We also compare our results with the ones obtained by other metaheuristics. The obtained results show that the proposed approach can achieve better quality solutions than some of the other algorithms found in the literature. These solutions can lead to better solutions to real problems that can be modeled with the 0-1 MKP.

Partially supported by CNPq and CAPES.

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Authors and Affiliations

  1. Faculty of Computing, Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil

    Bianca de Almeida Dantas & Edson Norberto Cáceres

Authors
  1. Bianca de Almeida Dantas
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  2. Edson Norberto Cáceres
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Corresponding author

Correspondence to Bianca de Almeida Dantas .

Editor information

Editors and Affiliations

  1. University of Perugia , Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata , Potenza, Italy

    Beniamino Murgante

  3. Covenant University , Ota, Nigeria

    Sanjay Misra

  4. University of Minho , Braga, Portugal

    Ana Maria A.C. Rocha

  5. Polytechnic University , Bari, Italy

    Carmelo M. Torre

  6. Monash University , Clayton, Victoria, Australia

    David Taniar

  7. Kyushu Sangyo University , Fukuoka, Japan

    Bernady O. Apduhan

  8. Saint Petersburg State University , Saint Petersburg, Russia

    Elena Stankova

  9. Beijing University of Posts & Telecommunication , Beijing, China

    Shangguang Wang

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de Almeida Dantas, B., Cáceres, E.N. (2016). Sequential and Parallel Hybrid Approaches of Augmented Neural Networks and GRASP for the 0-1 Multidimensional Knapsack Problem. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9787. Springer, Cham. https://doi.org/10.1007/978-3-319-42108-7_16

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  • DOI: https://doi.org/10.1007/978-3-319-42108-7_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42107-0

  • Online ISBN: 978-3-319-42108-7

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