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Parallel MOEA/D-ACO on GPU

  • Murilo Zangari de SouzaEmail author
  • Aurora Trinidad Ramirez Pozo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8864)

Abstract

This paper describes the idea of MOEA/D-ACO (Multiobjective Evolutionary Algorithm based on Decomposition and Ant Colony Optimization) and proposes a Graphics Processing Unit (GPU) implementation of MOEA/D-ACO using NVIDIA CUDA (Compute Unified Device Architecture) in order to improve the execution time. ACO is well-suited to GPU implementation, and both the solution construction and pheromone update phase are implemented using a data parallel approach. The parallel implementation is applied on the Multiobjective 0-1 Knapsack Problem and the Multiobjective Traveling Salesman Problem and reports speedups up to 19x and 11x respectively from the sequential counterpart with similar quality results. Moreover, the results show that the size of test instances, the number of objectives and the number of subproblems directly affect the speedup.

Keywords

MOEA/D-ACO GPU NVIDIA CUDA Multiobjective 0-1 knapsack problem Multiobjective traveling salesman problem 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Murilo Zangari de Souza
    • 1
    Email author
  • Aurora Trinidad Ramirez Pozo
    • 1
  1. 1.DInf, Federal University of ParanaCuritibaBrazil

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