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A Set-Associated Bin Packing Algorithm with Multiple Objectives in the Cloud

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Cognitive Computing – ICCC 2018 (ICCC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10971))

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Abstract

The bin packing problem (BPP) is NP-hard and it is widely studied due to its various applications, where the initial sole object is to find a minimum number of bins for the items. This paper applies the BPP in the cloud, and tries to attain multiple objectives, such as minimum used bins, minimum packing time and load balance for the bins. Therefore, a set-associative bin packing algorithm is proposed, where the item set is first divided into two sets with descending order, and then a two-way set-associative mapping process is used to combine the elements in divided sets and pack them into a suitable bin. The packing process is iterated until all the items are resolved. With different performance indicators, experiments and analysis are carried out by the comparison with the traditional typical packing algorithms, which verifies the efficiency of the algorithm.

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References

  1. Coffman Jr., E.G., Csirik, J., Galambos, G., Martello, S., Vigo, D.: Bin packing approximation algorithms: survey and classification. In: Handbook of Combinatorial Optimization, pp. 455–531. Kluwer Academic Publishers (2013)

    Chapter  Google Scholar 

  2. Dokeroglu, T., Cosar, A.: Optimization of one-dimensional bin packing problem with island parallel grouping genetic algorithms. Comput. Ind. Eng. 75, 176–186 (2014)

    Article  Google Scholar 

  3. Garey, M.R., Johnson, D.S.: Approximation algorithms for bin packing problems: a survey. In: Ausiello, G., Lucertini, M. (eds.) Analysis and Design of Algorithms in Combinatorial Optimization. ICMS, vol. 266, pp. 147–172. Springer, Vienna (1981). https://doi.org/10.1007/978-3-7091-2748-3_8

    Chapter  Google Scholar 

  4. Naderi, B., Yazdani, M.: A real multi-objective bin packing problem: a case study of an engine assembly line. Arab. J. Sci. Eng. 39(6), 5271–5277 (2014)

    Article  Google Scholar 

  5. Boyar, J., Favrholdt, L.M.: The relative worst order ratio for online algorithms. ACM Trans. Algorithms 3, 1–24 (2007)

    Article  MathSciNet  Google Scholar 

  6. Boyar, J., Epstein, L., Levin, A.: Tight results for next fit and worst fit with resource augmentation. Theor. Comput. Sci. 411, 2572–2580 (2010)

    Article  MathSciNet  Google Scholar 

  7. Martello, S., Toth, P.: Knapsack Problems: Algorithms and Computer Implementations. Wiley, Chichester (1990)

    MATH  Google Scholar 

  8. Scholl, A., Klein, R., Jurgens, C.: Bison: a fast hybrid procedure for exactly solving the one-dimensional bin packing problem. Comput. Oper. Res. 24(7), 627–645 (1997)

    Article  Google Scholar 

  9. Schwerin, P., Wscher, G.: A new lower bound for the bin-packing problem and its integration into MTP and bison. Pesqui. Op. 19, 111–129 (1999)

    Google Scholar 

  10. de Valerio Carvalho, J.M.: Exact solution of bin-packing problems using column generation and branch-and-bound. Ann. Oper. Res. 86, 629–659 (1999)

    Article  MathSciNet  Google Scholar 

  11. Gupta, J.N.D., Ho, J.C.: A new heuristic algorithm for the one-dimensional bin packing problem. Prod. Plann. Control 10, 598–603 (1999)

    Article  Google Scholar 

  12. Fleszar, K., Hindi, K.S.: New heuristics for one-dimensional bin-packing. Comput. Oper. Res. 29, 821–839 (2002)

    Article  Google Scholar 

  13. Masson, R., Vidal, T., Michallet, J., Penna, P.H.V., Petrucci, V., Subramanian, A., et al.: An iterated local search heuristic for multi-capacity bin packing and machine reassignment problems. Expert Syst. Appl. 40(13), 5266–5275 (2013)

    Article  Google Scholar 

  14. Alvim, A.C.F., Ribeiro, C.C.: A Hybrid bin-packing heuristic to multiprocessor scheduling. In: Ribeiro, C.C., Martins, S.L. (eds.) WEA 2004. LNCS, vol. 3059, pp. 1–13. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24838-5_1

    Chapter  Google Scholar 

  15. Singh, A., Gupta, A.K.: Two heuristics for the one-dimensional bin-packing problem. OR Spectr. 29(4), 765–781 (2007)

    Article  MathSciNet  Google Scholar 

  16. Loh, K.H., Golden, B., Wasil, E.: Solving the one-dimensional bin packing problem with a weight annealing heuristic. Comput. Oper. Res. 35(7), 2283–2291 (2008)

    Article  MathSciNet  Google Scholar 

  17. Fleszar, K., Charalambous, C.: Average-weight-controlled bin-oriented heuristics for the one-dimensional bin-packing problem. Eur. J. Oper. Res. 210, 176–184 (2011)

    Article  MathSciNet  Google Scholar 

  18. Quiroz-Castellanos, M., Cruz-Reyes, L., Torres-Jiménez, J., GomezSantill, C., Huacuja, H.J.F., Alvim, A.C.F.: A grouping genetic algorithm with controlled gene transmission for the bin packing problem. Comput. Oper. Res. 55, 52–64 (2015)

    Article  MathSciNet  Google Scholar 

  19. Brando, F., Pedroso, J.P.: Bin Packing and Related Problems: General Arc-flow Formulation with Graph Compression, Technical Report DCC-2013-08, Faculdade de Ciênciasda Universidadedo Porto, Portugal (2013)

    Google Scholar 

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Acknowledgments

This paper is supported by China Ministry of Education Online Education Research Center Online Education Fund (pervasive education) (No. 2017YB122), the Nature Science Fund of China (NSFC) (No. 61472139).

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Authors and Affiliations

  1. School of Information and Engineering, East China University of Science and Technology, Shanghai, China

    Fei Luo & Chunhua Gu

Authors
  1. Fei Luo
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  2. Chunhua Gu
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Corresponding author

Correspondence to Fei Luo .

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Editors and Affiliations

  1. Big Data Platform Division, Peking, China

    Jing Xiao

  2. University of Pittsburgh, Pittsburgh, Pennsylvania, USA

    Zhi-Hong Mao

  3. IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA

    Toyotaro Suzumura

  4. Kingdee International Software Group Co., Ltd., Shenzhen, China

    Liang-Jie Zhang

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Luo, F., Gu, C. (2018). A Set-Associated Bin Packing Algorithm with Multiple Objectives in the Cloud. In: Xiao, J., Mao, ZH., Suzumura, T., Zhang, LJ. (eds) Cognitive Computing – ICCC 2018. ICCC 2018. Lecture Notes in Computer Science(), vol 10971. Springer, Cham. https://doi.org/10.1007/978-3-319-94307-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-94307-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94306-0

  • Online ISBN: 978-3-319-94307-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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