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      A Parallel Genetic Algorithm for Three Dimensional Bin Packing with Heterogeneous Bins

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          Abstract

          This paper presents a parallel genetic algorithm for three dimensional bin packing with heterogeneous bins using Hadoop Map-Reduce framework. The most common three dimensional bin packing problem which packs given set of boxes into minimum number of equal sized bins is proven to be NP Hard. The variation of three dimensional bin packing problem that allows heterogeneous bin sizes and rotation of boxes is computationally more harder than common three dimensional bin packing problem. The proposed Map-Reduce implementation helps to run the genetic algorithm for three dimensional bin packing with heterogeneous bins on multiple machines parallely and computes the solution in relatively short time.

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          Author and article information

          Journal
          17 November 2014
          Article
          10.14445/22312803/IJCTT-V17P108
          1411.4565
          b9948120-91db-4385-bda8-fccdb94e4ea1

          http://creativecommons.org/licenses/by-nc-sa/3.0/

          History
          Custom metadata
          International Journal of Computer Trends and Technology (IJCTT) V17(1):33-38, Nov 2014
          6 pages, 4 figures
          cs.DC cs.NE

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