Skip to main content
SpringerLink
Log in
Book cover

International Conference on Internet and Distributed Computing Systems

IDCS 2016: Internet and Distributed Computing Systems pp 206–213Cite as

Multi-objective Optimization of Warehouse System Based on the Genetic Algorithm

  • Conference paper
  • First Online:

  • 1718 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9864))

Abstract

As a unit of modern warehouse, the Automated Storage/Retrieval system(AS/RS) plays an important role in modern logistic system. Especially in case of thousands of goods locations, the slotting optimization of warehouse storage system is a crucial step to improve the access efficiency and to reduce the operating costs. With the tiered warehouse as the research subject, this paper firstly analyzed and extracted the key information of related goods location optimization in the warehouse management information system. Then a space optimization model was built, with goods turnover efficiency and stabilities being set as research objectives. By using the MATLAB genetic algorithm toolbox, the multi-objective optimization and simulation of the warehouse system is conducted. Through comparison and analysis of optimization results, the algorithm is finally proved to be applicable.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Poulos, P.N., Rigatos, G.G., Tzafestas, S.G., Koukos, A.K.: A pareto-optimal genetic algorithm for warehouse multi-objective optimization. Eng. Appl. Artif. Intell. 6(14), 737–749 (2001)

    Article  Google Scholar 

  2. Gu, J., Goetschalckx, M., McGinnis, L.F.: Research on warehouse design and performance evaluation: a comprehensive review. Eur. J. Oper. Res. 203(3), 539–549 (2010)

    Article  MATH  Google Scholar 

  3. Larson, T.N., March, H., Kusiak, A.: A heuristic approach to warehouse layout with class based storage. IIE Trans. 29(4), 337–348 (1997)

    Google Scholar 

  4. Lai, K.K., Xue, J., Zhang, G.: Layout design for a paper reel warehouse: a two-stage heuristic approach. Int. J. Prod. Econ. 75(3), 231–243 (2002)

    Article  Google Scholar 

  5. Sooksaksun, N., Kachitvichyanukul, V.: Particle swarm optimization for warehouse design problem. In: Proceedings of the 11th Conference Asia Pacific Industrial Engineering and Management Systems(APIEMS), Melaka, Malaysia, pp. 1–6 (2010)

    Google Scholar 

  6. Li, M., Chen, X., Liu, C.: Pareto and niche genetic algorithm for storage location assignment optimization problem. In: Proceedings of the 3rd International Conference Innovative Computing Information and Control (ICICIC), Dalian, China, pp. 465–468 (2008)

    Google Scholar 

  7. Sooksaksun, N.: Pareto-based multi-objective optimization for two-block class-based storage warehouse design. Indus. Eng. Manage. Syst. 11(4), 331–338 (2012)

    Google Scholar 

  8. Cai, H., Aref, A.J.: A genetic algorithm-based multi-objective optimization for hybrid fiber reinforced polymeric deck and cable system of cable-stayed bridges. Struct. Multidisc. Optim. 52(3), 583–594 (2015)

    Article  Google Scholar 

  9. Hirsch, C., Shukla, P.K., Schmeck, H.: Variable preference modeling using multi-objective evolutionary algorithms. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds.) EMO 2011. LNCS, vol. 6576, pp. 91–105. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  10. Djeffal, F.: Multi-objective genetic algorithms based approach to optimize the electrical performances of the gate stack double gate (GSDG) MOSFET. Microelectron. J. 42(5), 661–666 (2011)

    Article  Google Scholar 

  11. Lins, I.D.: Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation. Simul. Modell. Pract. Theor. 19(1), 362–381 (2011)

    Article  Google Scholar 

  12. Perez, E.B., Carvalho, M.S.: Optimization of slot-coating processes: minimizing the amplitude of film-thickness oscillation. J. Eng. Math. 71(71), 97–108 (2011)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. City College of WUST, Wuhan, China

    Ting Wu, Hao Wang & Zhe Yuan

Authors
  1. Ting Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhe Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ting Wu .

Editor information

Editors and Affiliations

  1. Wuhan University of Technology , Wuhan, China

    Wenfeng Li

  2. Central Queensland University , North Rockhampton, Queensland, Australia

    Shawkat Ali

  3. Delft University of Technology , Delft, The Netherlands

    Gabriel Lodewijks

  4. University of Calabria , Rende (CS), Italy

    Giancarlo Fortino

  5. University of Reading , Reading, United Kingdom

    Giuseppe Di Fatta

  6. Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

  7. CSIRO ICT , Acton, Australia

    Mukaddim Pathan

  8. ICAR-CNR, Rende (CS), Italy

    Antonio Guerrieri

  9. Wuhan University of Technology , Wuhan, China

    Qiang Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Wu, T., Wang, H., Yuan, Z. (2016). Multi-objective Optimization of Warehouse System Based on the Genetic Algorithm. In: Li, W., et al. Internet and Distributed Computing Systems. IDCS 2016. Lecture Notes in Computer Science(), vol 9864. Springer, Cham. https://doi.org/10.1007/978-3-319-45940-0_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-45940-0_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45939-4

  • Online ISBN: 978-3-319-45940-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation